Therapeutic window determination

ABSTRACT

A therapeutic window for at least one electrode of a medical system may be determined based on a volume of tissue expected to be activated (“VTA”) by electrical stimulation delivered by the at least one electrode. In some examples, a processor determines the therapeutic window for a particular electrode by at least determining an efficacy threshold based on the VTA expected to result from the delivery of electrical stimulation according to a set of electrical stimulation parameter values including the stimulation parameter at the efficacy threshold, and determining an adverse-effects threshold based on the VTA expected to result from the delivery of electrical stimulation according to a set of electrical stimulation parameter values including the stimulation parameter at the adverse-effects threshold.

This application is a continuation of U.S. patent application Ser. No.14/195,489, entitled, “THERAPEUTIC WINDOW DETERMINATION,” which wasfiled on Mar. 3, 2014 and issued on Oct. 4, 2016 as U.S. Pat. No.9,457,188. The entire content of U.S. patent application Ser. No.14/195,489 is incorporated herein by reference.

TECHNICAL FIELD

The disclosure relates to electrical stimulation therapy.

BACKGROUND

Implantable medical devices, such as electrical stimulators ortherapeutic agent delivery devices, have been proposed for use indifferent therapeutic applications, such as deep brain stimulation(DBS), spinal cord stimulation (SCS), pelvic stimulation, gastricstimulation, peripheral nerve stimulation, functional electricalstimulation or delivery of pharmaceutical agent, insulin, pain relievingagent or anti-inflammatory agent to a target tissue site within apatient. In some therapy systems, an implantable electrical stimulatordelivers electrical therapy to a target tissue site within a patientwith the aid of one or more electrodes, which may be deployed by medicalleads, on a housing of the electrical stimulator, or both.

During a programming session, which may occur during implant of themedical device, during a trial session, or during an in-clinic or remotefollow-up session after the medical device is implanted in the patient,a clinician may generate one or more therapy programs (also referred toas therapy parameter sets) that provide efficacious therapy to thepatient, where each therapy program may define values for a set oftherapy parameters. A medical device may deliver therapy to a patientaccording to one or more stored therapy programs. In the case ofelectrical stimulation, the therapy parameters may definecharacteristics of the electrical stimulation waveform to be delivered.In examples in which electrical stimulation is delivered in the form ofelectrical pulses, for example, the therapy parameters may include anelectrode combination, an amplitude, which may be a current or voltageamplitude, a pulse width, and a pulse rate.

SUMMARY

The disclosure describes example systems, devices, and methods fordetermining, for at least one electrode of a medical system, a range ofelectrical stimulation parameter values that may provide efficacioustherapy to a patient when electrical stimulation is delivered to thepatient with the at least one electrode. The range of electricalstimulation parameter values may also be referred to as a therapeuticwindow. In some examples, a therapeutic window is defined as the valuesof an electrical stimulation parameter between an efficacy threshold,which may be the lowest electrical stimulation parameter value (orhighest, depending on the parameter) at which efficacious effects of theelectrical stimulation were first observed, and an adverse-effectsthreshold, which may be the lowest electrical stimulation parametervalue (or highest, depending on the parameter) at which adverse effectsof the electrical stimulation were first observed. In some examples, thetherapeutic window includes the efficacy threshold, but does not includethe adverse-effects threshold.

In some examples, a processor of a device (e.g., a medical deviceprogrammer or a medical device) determines the therapeutic window for anelectrode based on a volume of tissue expected to be activated byelectrical stimulation delivered by the electrode, which may also bereferred to as a volume of tissue activation (“VTA”). The processor maydetermine a VTA for a particular electrode and a set of electricalstimulation parameter values using a modeling algorithm that is based oncharacteristics of the tissue of the patient proximate the one or moreelectrodes. In this way, the VTA may be estimated. In some examples, theprocessor automatically determines the therapeutic window for aparticular electrode by at least determining a first value of anelectrical stimulation parameter at which a VTA is expected to firstoverlap with one or more regions of tissue of the patient associatedwith efficacious electrical stimulation therapy. The overlap may be, forexample, overlap sufficient to cause one or more efficacious effects ofelectrical stimulation. This first value may be an efficacy thresholdvalue. The processor may also automatically determine a second value ofthe electrical stimulation parameter at which a VTA is expected to firstoverlap with one or more regions of tissue of the patient associatedwith one or more adverse effects of electrical stimulation therapy. Theoverlap may be, for example, overlap sufficient to cause one or moreadverse effects of electrical stimulation. This second value may be anadverse-effects threshold.

In accordance with some examples, a therapeutic window is determined foreach electrode of a plurality of electrodes of a lead. The plurality ofdetermined therapeutic windows may help a clinician determine whichelectrodes to use in programming the electrical stimulation therapy forthe patient, e.g., which electrodes may provide efficacious therapy withrelatively minimal side effects.

In one example, the disclosure is directed to a method comprisingdetermining, by a processor, an efficacy threshold value of at least oneelectrical stimulation parameter based a first volume of tissueactivation expected to result from delivery of electrical stimulation byat least one electrode to a patient, and determining, by the processor,an adverse-effects threshold value of the at least one stimulationparameter based on second volume of tissue activation expected to resultfrom delivery of electrical stimulation by the at least one electrode tothe patient.

In another example, the disclosure is directed to a system comprising amemory, and a processor configured to determine an efficacy thresholdvalue of at least one stimulation parameter based a volume of tissueactivation expected to result from delivery of electrical stimulation byat least one electrode to a patient, to determine an adverse-effectsthreshold value of the at least one stimulation parameter based onsecond volume of tissue activation expected to result from delivery ofelectrical stimulation by the at least one electrode to the patient, andto store the efficacy threshold value and the adverse-effects thresholdvalue in the memory.

In another example, the disclosure is directed to a system comprisingmeans for determining an efficacy threshold value of at least oneelectrical stimulation parameter based a first volume of tissueactivation expected to result from delivery of electrical stimulation byat least one electrode to a patient, and means for determining anadverse-effects threshold value of the at least one stimulationparameter based on second volume of tissue activation expected to resultfrom delivery of electrical stimulation by the at least one electrode tothe patient.

In another example, the disclosure is directed to a computer-readablemedium comprising instructions that, when executed, cause a processor todetermine an efficacy threshold value of at least one electricalstimulation parameter based a first volume of tissue activation expectedto result from delivery of electrical stimulation by at least oneelectrode to a patient, and determine an adverse-effects threshold valueof the at least one stimulation parameter based on a second volume oftissue activation expected to result from delivery of electricalstimulation by the at least one electrode to the patient.

In another aspect, the disclosure is directed to a computer-readablestorage medium, which may be an article of manufacture. Thecomputer-readable storage medium includes computer-readable instructionsfor execution by one or more processors. The instructions cause one ormore processors to perform any part of the techniques described herein.The instructions may be, for example, software instructions, such asthose used to define a software or computer program.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages will be apparent from the description and drawings, and fromthe claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram illustrating an example deep brainstimulation (DBS) system configured to sense a bioelectrical brainsignal and deliver electrical stimulation therapy to a tissue sitewithin a brain of a patient.

FIG. 2 is functional block diagram illustrating components of an examplemedical device.

FIG. 3 is a functional block diagram illustrating components of anexample medical device programmer.

FIG. 4 is a flow diagram illustrating an example technique fordetermining a therapeutic window for at least one electrode of a therapysystem

FIG. 5 is a flow diagram illustrating an example technique fordetermining whether a volume of tissue activation overlaps with aparticular region of tissue.

FIG. 6 is a flow diagram illustrating an example technique fordetermining a volume of tissue activation.

FIG. 7 is a flow diagram illustrating another example technique fordetermining efficacy and adverse-effects thresholds for at least oneelectrode of a therapy system.

FIG. 8 is a flow diagram illustrating an example technique fordetermining a therapeutic window for an electrode.

DETAILED DESCRIPTION

The disclosure describes example systems, devices, and methods fordetermining, for at least one electrode of a medical system, atherapeutic window based on a volume of tissue expected to be activatedby electrical stimulation delivered via the at least one electrode. Theat least one electrode can be, for example, an electrode of a lead or amedical device housing. In some examples, an electrode may also bereferred to as a “contact” or an “electrical contact.” In some examples,tissue may be “activated” when the electrical stimulation causes anaction potential to propagate along a neuron of the tissue, which mayindicate that the transmembrane potential of the neuron reached aparticular level, such as a potential greater than 0 mV.

The therapeutic window may be a range of values for one or moreelectrical stimulation parameters, where therapy delivery in accordancewith the values within the range may provide efficacious therapy to thepatient. In some examples, a therapeutic window is defined as the valuesof an electrical stimulation parameter between an efficacy thresholdvalue (also referred to herein as an “efficacy threshold”) and anadverse-effects threshold value (also referred to herein as an“adverse-effects threshold.” In some examples, the lower bound of thetherapeutic window may include the efficacy threshold, and the upperbound may be defined by, but not include, the adverse-effects threshold.In other examples, the lower bound of the therapeutic window includesthe efficacy threshold and the upper bound includes the adverse-effectsthreshold. In yet other examples, the upper bound of the therapeuticwindow may be defined by the efficacy threshold and the lower bound maybe defined by the adverse-effects threshold. In these examples, theupper bound may, or may not, include the efficacy threshold.

An efficacy threshold may be the electrical stimulation parameter valueat which the electrical stimulation therapy may first yield someefficacy, e.g., as the parameter value is increased or decreased, forthe patient and an adverse-effects threshold may be the first electricalstimulation parameter value at which the electrical stimulation therapymay first yield an adverse effect for the patient, e.g., as theparameter value is increased or decreased. The results indicative ofefficacy can include, for example, a decrease in the severity,frequency, or both, of one or more symptoms of the patient condition forwhich the therapy system is implemented to address. Adverse effects caninclude, for example, any side effect or non-therapeutic effect that thepatient or clinician may consider to adversely impact the benefits ofthe therapy delivery. For example, depending on the patient condition,adverse effects can include muscle contractions or other undesirablemuscle recruitment, discomfort, tremors, paresthesia in one or moreparts of the body of the patient, and the like.

In some examples described herein, a processor of a device (e.g., amedical device programmer) determines the therapeutic window for aparticular electrode by at least determining an efficacy threshold basedon the VTA expected to result from the delivery of electricalstimulation according to a set of electrical stimulation parametervalues including the stimulation parameter at the efficacy threshold,and determining the adverse-effects threshold based on the VTA expectedto result from the delivery of electrical stimulation according to a setof electrical stimulation parameter values including the stimulationparameter at the adverse-effects threshold.

For example, for a particular electrode, the processor may determine aninitial VTA based on a set of electrical stimulation parameter values,where the initial VTA is a starting point for the determination of thetherapeutic window. The processor may then adjust (e.g., increase ordecrease in predetermined increments) the value of at least one of thestimulation parameters of the set until the resulting VTA overlaps withone or more regions of tissue within the patient associated withefficacious results, e.g., in an amount sufficient to cause theefficacious effects. This value may be the efficacy threshold, and theregions of tissue may be referred to as efficacy regions. The processormay then continuing adjusting the value of the at least one stimulationparameter (e.g., in predetermined increments) until the resulting VTAoverlaps with one or more regions of tissue within the patientassociated with adverse effects, e.g., in an amount sufficient to causethe adverse effects. This value may be the adverse-effects threshold,and the regions of tissue may be referred to as adverse-effects regions.The efficacy regions and adverse-effects regions may bethree-dimensional regions (e.g., volumes) of tissue.

The amount of commonality in space between the VTA and the one or moreregions of tissue required to constitute an overlap, as the term is usedherein, may differ based on various factors, including the region oftissue to which electrical stimulation is applied. For example, anoverlap may more than a mere point (e.g., a square millimeter) in commonbetween the VTA and the one or more regions of tissue. Thus, in somecases, the overlap may also be referred to as a “sufficient” overlap, inthat the overlap is in an amount sufficient to cause the efficaciouseffects or adverse effects, or a “significant overlap,” in that theoverlap is significant enough to cause the efficacious effects oradverse effects. Thus, while the term “overlap” is primarily referred toherein, the discussed overlap can also refer to a sufficient overlap ora significant overlap.

Example efficacy and adverse-effects regions of tissue can include, forexample, anatomical structures of the brain, specific muscles or musclegroups, clinician-defined regions of the patient's body, e.g., adjacentthe spinal cord or peripheral nerves, and the like. As discussed infurther detail below, the one or more regions of tissue used todetermine the therapeutic windows may be selected based on informationspecific to the patient or to a group of patients.

The one or more efficacy regions may include tissue that, when activatedby electrical stimulation, elicits a therapeutic benefit or result forthe patient, e.g., by mitigating one or more symptoms of a patientcondition, reducing a frequency of the occurrence of one or moresymptoms or patient events associated with the patient condition, orboth. The particular therapeutic benefit or result that is used todetermine the efficacious results may differ based on the patientcondition or the patient or clinician preferences. If there are multipleefficacy regions with which the VTA is compared to determine whetherthere is overlap, the regions may be directly adjacent to each other insome examples, e.g., depending on the patient condition, and may beseparated by one or more other regions of tissue in other examples.

The one or more adverse-effects regions of tissue may include tissuethat, when activated by electrical stimulation, causes one or more sideeffects. The particular adverse effects that are used to determine thesecond region may also differ based on the patient condition or thepatient or clinician preferences. As with the efficacy regions, if thereare multiple adverse-effects regions of tissue, the regions may bedirectly adjacent to each other in some examples, and may be separatedby one or more other regions of tissue in other examples.

In some examples, a processor automatically determines the therapeuticwindow for each electrode of a plurality of electrodes based on thevolume of tissue expected to be activated by electrical stimulationdelivered via the respective electrode in a unipolar stimulationconfiguration. In a unipolar configuration, the active electrode withwhich electrical stimulation signals are delivered is referenced to anelectrode carried by the implantable medical device housing or “can.”The processor may associate the therapeutic windows with the respectiveelectrodes in a memory. In some examples, the processor may generate agraphical user interface that includes a list of electrodes and therespective therapeutic windows, or, in some examples, a list ofelectrodes and the respective efficacy thresholds and adverse-effectsthreshold.

As part of the programming of an electrical stimulation therapy system,a clinician may select one or more electrode combinations that mayprovide efficacious therapy to a patient. The electrodes of theelectrode combinations may, for example, be selected based on aproximity to a target therapy delivery site, based on a distance fromone or more adverse-effects regions of tissue, or both. Therapeuticwindows of electrodes may provide a basis for comparing the potentialbenefits of a plurality of electrodes. For example, the therapeuticwindow of a particular electrode may indicate whether the electrode maybe useful for providing efficacious stimulation therapy to a patient,e.g., by indicating the electrodes that may provide a relatively highefficacy and relative low risk of side effects. Thus, informationindicating the therapeutic windows for a plurality of electrodes mayhelp aid the selection of one or more electrode combinations that mayprovide efficacious electrical stimulation therapy to a patient. Forexample, an electrode associated with a relatively large therapeuticwindow (e.g., as indicated by the difference between the electricalstimulation parameter values bounding the therapeutic window) mayindicate that the electrode will provide more latitude to findefficacious electrical stimulation parameter values for the patient.Determination of a therapeutic window in accordance with the techniquesdescribed herein may help a user program electrical stimulationparameters for electrical stimulation therapy delivered by an electricalstimulator in an efficient manner.

In some examples, a therapeutic window may define bounds for just oneelectrical stimulation parameter, e.g., amplitude, assumingsubstantially fixed (e.g., fixed or nearly fixed) levels or ranges forthe other electrical stimulation parameters. In other examples, atherapy window may define bounds of values for combinations ofelectrical stimulation parameters.

FIG. 1 is a conceptual diagram illustrating an example therapy system 10that is configured to deliver therapy to patient 12 to manage a disorderof patient 12. Patient 12 ordinarily will be a human patient. In somecases, however, therapy system 10 may be applied to other mammalian ornon-mammalian non-human patients. In the example shown in FIG. 1,therapy system 10 includes medical device programmer 14, implantablemedical device (IMD) 16, lead extension 18, and one or more leads 20Aand 20B (collectively “leads 20”) with respective sets of electrodes 24,26. IMD 16 includes a stimulation generator configured to generate anddeliver electrical stimulation therapy to one or more regions of brain28 of patient 12 via one or more electrodes 24, 26 of leads 20A and 20B,respectively.

In the example shown in FIG. 1, therapy system 10 may be referred to asa deep brain stimulation (DBS) system because IMD 16 is configured todeliver electrical stimulation therapy directly to tissue within brain28, e.g., a tissue site under the dura mater of brain 28 or one or morebranches or nodes, or a confluence of fiber tracks. In other examples,leads 20 may be positioned to deliver therapy to a surface of brain 28(e.g., the cortical surface of brain 28). For example, in some examples,IMD 16 may provide cortical stimulation therapy to patient 12, e.g., bydelivering electrical stimulation to one or more tissue sites in thecortex of brain 28. As another example, IMD 16 may provide vagal nervestimulation (VNS) therapy to patient 12 by delivering electricalstimulation to one or more vagal nerve tissue sites.

DBS may be used to treat or manage various patient conditions, such as,but not limited to, seizure disorders (e.g., epilepsy), pain, migraineheadaches, psychiatric disorders (e.g., major depressive disorder (MDD),bipolar disorder, anxiety disorders, post traumatic stress disorder,dysthymic disorder, and obsessive compulsive disorder (OCD), behaviordisorders, mood disorders, memory disorders, mentation disorders,movement disorders (e.g., essential tremor or Parkinson's disease),Huntington's disease, Alzheimer's disease, or other neurological orpsychiatric disorders and impairment of patient 12.

Therapy systems configured for treatment of other patient conditions viadelivery of therapy to brain 28 or another suitable target therapydelivery site in patient 12 can also be used in accordance with thetechniques for determining one or more therapeutic windows disclosedherein. For example, in other applications of therapy system 10, thetarget therapy delivery site within patient 12 may be a locationproximate to a spinal cord or sacral nerves (e.g., the S2, S3 or S4sacral nerves) in patient 12 or any other suitable nerve, organ, muscleor muscle group in patient 12, which may be selected based on, forexample, a patient condition. For example, therapy system 10 may be usedto deliver electrical stimulation or a therapeutic agent to tissueproximate to a pudendal nerve, a perineal nerve or other areas of thenervous system, in which cases, leads 20 would be implanted andsubstantially fixed proximate to the respective nerve. As furtherexamples, an electrical stimulation system may be positioned to delivera stimulation to help manage peripheral neuropathy or post-operativepain mitigation, ilioinguinal nerve stimulation, intercostal nervestimulation, gastric stimulation for the treatment of gastric mobilitydisorders and obesity, muscle stimulation, for mitigation of otherperipheral and localized pain (e.g., leg pain or back pain).

In the example shown in FIG. 1, IMD 16 may be implanted within asubcutaneous pocket in the pectoral region of patient 12. In otherexamples, IMD 16 may be implanted within other regions of patient 12,such as a subcutaneous pocket in the abdomen or buttocks of patient 12or proximate the cranium of patient 12. Implanted lead extension 18 iscoupled to IMD 16 via connector block 30 (also referred to as a header),which may include, for example, electrical contacts that electricallycouple to respective electrical contacts on lead extension 18. Theelectrical contacts electrically couple the electrodes 24, 26 carried byleads 20 to IMD 16. Lead extension 18 traverses from the implant site ofIMD 16 within a chest cavity of patient 12, along the neck of patient 12and through the cranium of patient 12 to access brain 28. IMD 16 can beconstructed of a biocompatible material that resists corrosion anddegradation from bodily fluids. IMD 16 may comprise a hermetic housing34 to substantially enclose components, such as a processor, a therapymodule, and memory.

In the example shown in FIG. 1, leads 20 are implanted within the rightand left hemispheres, respectively, of brain 28 in order to deliverelectrical stimulation to one or more regions of brain 28, which may beselected based on many factors, such as the type of patient conditionfor which therapy system 10 is implemented to manage. Other implantsites for leads 20 and IMD 16 are contemplated. For example, IMD 16 maybe implanted on or within cranium 32 or leads 20 may be implanted withinthe same hemisphere at multiple target tissue sites or IMD 16 may becoupled to a single lead that is implanted in one or both hemispheres ofbrain 28.

Leads 20 may be positioned to deliver electrical stimulation to one ormore target tissue sites within brain 28 to manage patient symptomsassociated with a disorder of patient 12. Leads 20 may be implanted toposition electrodes 24, 26 at desired locations of brain 28 via anysuitable technique, such as through respective burr holes in the skullof patient 12 or through a common burr hole in the cranium 32. Leads 20may be placed at any location within brain 28 such that electrodes 24,26 are capable of providing electrical stimulation to target therapydelivery sites within brain 28 during treatment. Different neurologicalor psychiatric disorders may be associated with activity in one or moreof regions of brain 28, which may differ between patients. Accordingly,the target therapy delivery site for electrical stimulation therapydelivered by leads 20 may be selected based on the patient condition.For example, a suitable target therapy delivery site within brain 28 forcontrolling a movement disorder of patient 12 may include one or more ofthe pedunculopontine nucleus (PPN), thalamus, basal ganglia structures(e.g., globus pallidus, substantia nigra or subthalamic nucleus), zonainserta, fiber tracts, lenticular fasciculus (and branches thereof),ansa lenticularis, or the Field of Forel (thalamic fasciculus). The PPNmay also be referred to as the pedunculopontine tegmental nucleus.

As another example, in the case of MDD, bipolar disorder, OCD, or otheranxiety disorders, leads 20 may be implanted to deliver electricalstimulation to the anterior limb of the internal capsule of brain 28,and only the ventral portion of the anterior limb of the internalcapsule (also referred to as a VC/VS), the subgenual component of thecingulate cortex (which may be referred to as CG25), anterior cingulatecortex Brodmann areas 32 and 24, various parts of the prefrontal cortex,including the dorsal lateral and medial pre-frontal cortex (PFC) (e.g.,Brodmann area 9), ventromedial prefrontal cortex (e.g., Brodmann area10), the lateral and medial orbitofrontal cortex (e.g., Brodmann area11), the medial or nucleus accumbens, thalamus, intralaminar thalamicnuclei, amygdala, hippocampus, the lateral hypothalamus, the Locusceruleus, the dorsal raphe nucleus, ventral tegmentum, the substantianigra, subthalamic nucleus, the inferior thalamic peduncle, the dorsalmedial nucleus of the thalamus, the habenula, the bed nucleus of thestria terminalis, or any combination thereof.

As another example, in the case of a seizure disorder or Alzheimer'sdisease, for example, leads 20 may be implanted to deliver electricalstimulation to regions within the Circuit of Papez, such as, e.g., oneor more of the anterior thalamic nucleus, the internal capsule, thecingulate, the fornix, the mammillary bodies, the mammillothalamic tract(mammillothalamic fasciculus), or the hippocampus. Target therapydelivery sites not located in brain 28 of patient 12 are alsocontemplated.

Although leads 20 are shown in FIG. 1 as being coupled to a common leadextension 18, in other examples, leads 20 may be coupled to IMD 16 viaseparate lead extensions or directly coupled to IMD 16. Moreover,although FIG. 1 illustrates system 10 as including two leads 20A and 20Bcoupled to IMD 16 via lead extension 18, in some examples, system 10 mayinclude one lead or more than two leads.

In the examples shown in FIG. 1, electrodes 24, 26 of leads 20 are shownas ring electrodes. Ring electrodes may be relatively easy to programand may be capable of delivering an electrical field to any tissueadjacent to leads 20. In other examples, electrodes 24, 26 of leads 20may have different configurations. For example, one or more of theelectrodes 24, 26 of leads 20 may have a complex electrode arraygeometry that is capable of producing shaped electrical fields,including interleaved stimulation. An example of a complex electrodearray geometry may include an array of electrodes positioned atdifferent axial positions along the length of a lead, as well as atdifferent angular positions about the periphery, e.g., circumference, ofthe lead. The complex electrode array geometry may include multipleelectrodes (e.g., partial ring or segmented electrodes) around theperimeter of each lead 20, in addition to, or instead of, a ringelectrode. In this manner, electrical stimulation may be directed to aspecific direction from leads 20 to enhance therapy efficacy and reducepossible adverse side effects from stimulating a large volume of tissue.

In some examples, outer housing 34 of IMD 16 may include one or morestimulation and/or sensing electrodes. For example, housing 34 cancomprise an electrically conductive material that is exposed to tissueof patient 12 when IMD 16 is implanted in patient 12, or an electrodecan be attached to housing 34. In other examples, leads 20 may haveshapes other than elongated cylinders as shown in FIG. 1 with active orpassive tip configurations. For example, leads 20 may be paddle leads,spherical leads, bendable leads, or any other type of shape effective intreating patient 12.

IMD 16 may deliver electrical stimulation therapy to brain 28 of patient12 according to one or more stimulation therapy programs. A stimulationtherapy program may define one or more electrical stimulation parametervalues for therapy generated by a stimulation generator of IMD 16 anddelivered from IMD 16 to a target therapy delivery site within patient12 via one or more electrodes 24, 26. The electrical stimulationparameters may define an aspect of the electrical stimulation therapy,and may include, for example, voltage or current amplitude of anelectrical stimulation signal, a charge level of an electricalstimulation, a frequency of the electrical stimulation signal, and, inthe case of electrical stimulation pulses, pulse rate, pulse width,waveform shape, and other appropriate parameters such as duration orduty cycle. In addition, if different electrodes are available fordelivery of stimulation, a therapy parameter of a therapy program may befurther characterized by an electrode combination, which may defineselected electrodes 24, 26 and their respective polarities. In someexamples, stimulation may be delivered using a continuous waveform andthe stimulation parameters may define this waveform.

In addition to being configured to deliver therapy to manage a disorderof patient 12, therapy system 10 may be configured to sensebioelectrical brain signals of patient 12. For example, IMD 16 mayinclude a sensing module that is configured to sense bioelectrical brainsignals within one or more regions of brain 28 via a subset ofelectrodes 24, 26, another set of electrodes, or both. Accordingly, insome examples, electrodes 24, 26 may be used to deliver electricalstimulation from the therapy module to target sites within brain 28 aswell as sense brain signals within brain 28. However, IMD 16 can alsouse a separate set of sensing electrodes to sense the bioelectricalbrain signals. In some examples, the sensing module of IMD 16 may sensebioelectrical brain signals via one or more of the electrodes 24, 26that are also used to deliver electrical stimulation to brain 28. Inother examples, one or more of electrodes 24, 26 may be used to sensebioelectrical brain signals while one or more different electrodes 24,26 may be used to deliver electrical stimulation.

External medical device programmer 14 is configured to wirelesslycommunicate with IMD 16 as needed to provide or retrieve therapyinformation. Programmer 14 is an external computing device that theuser, e.g., the clinician and/or patient 12, may use to communicate withIMD 16. For example, programmer 14 may be a clinician programmer thatthe clinician uses to communicate with IMD 16 and program one or moretherapy programs for IMD 16. In addition, or instead, programmer 14 maybe a patient programmer that allows patient 12 to select programs and/orview and modify therapy parameter values. The clinician programmer mayinclude more programming features than the patient programmer. In otherwords, more complex or sensitive tasks may only be allowed by theclinician programmer to prevent an untrained patient from makingundesired changes to IMD 16.

Programmer 14 may be a hand-held computing device with a displayviewable by the user and an interface for providing input to programmer14 (i.e., a user input mechanism). For example, programmer 14 mayinclude a small display screen (e.g., a liquid crystal display (LCD) ora light emitting diode (LED) display) that presents information to theuser. In addition, programmer 14 may include a touch screen display,keypad, buttons, a peripheral pointing device or another input mechanismthat allows the user to navigate though the user interface of programmer14 and provide input. If programmer 14 includes buttons and a keypad,the buttons may be dedicated to performing a certain function, e.g., apower button, the buttons and the keypad may be soft keys that change infunction depending upon the section of the user interface currentlyviewed by the user, or any combination thereof

In other examples, programmer 14 may be a larger workstation or aseparate application within another multi-function device, rather than adedicated computing device. For example, the multi-function device maybe a notebook computer, tablet computer, workstation, cellular phone,personal digital assistant or another computing device that may run anapplication that enables the computing device to operate as a securemedical device programmer 14. A wireless adapter coupled to thecomputing device may enable secure communication between the computingdevice and IMD 16.

When programmer 14 is configured for use by the clinician, programmer 14may be used to transmit programming information to IMD 16. Programminginformation may include, for example, hardware information, such as thetype of leads 20, the arrangement of electrodes 24, 26 on leads 20, theposition of leads 20 within brain 28, one or more therapy programsdefining therapy parameter values, therapeutic windows for one or moreelectrodes 24, 26, and any other information that may be useful forprogramming into IMD 16. Programmer 14 may also be capable of completingfunctional tests (e.g., measuring the impedance of electrodes 24, 26 ofleads 20).

The clinician may also generate and store therapy programs within IMD 16with the aid of programmer 14. During a programming session, theclinician may determine one or more therapy programs that may provideefficacious therapy to patient 12 to address symptoms associated withthe patient condition. For example, the clinician may select one or moreelectrode combinations with which stimulation is delivered to brain 28.During the programming session, patient 12 may provide feedback to theclinician as to the efficacy of the specific program being evaluated orthe clinician may evaluate the efficacy based on one or more sensed orobservable physiological parameters of patient (e.g., muscle activity)or based on motion detected via one or more motion sensors that generatesignals indicative of motion of patient 12. Programmer 14 may assist theclinician in the creation/identification of therapy programs byproviding a system for identifying potentially beneficial therapyparameter values.

As discussed in further detail below, in some examples, programmer 14(or another computing device) is configured to determine, for at leastone electrode (e.g., for each electrode 24, 26) of therapy system 10, atherapeutic window, and generate and display information regarding thedetermined therapeutic windows. For example, programmer 14 may generatea display that lists each electrode 24, 26, or a subset of electrodes24, 26, and, for each electrode, the respective therapeutic window. Thetherapeutic windows can be displayed as, for example, an efficacythreshold value and an adverse-effects threshold, which may define theboundaries of the therapeutic window in some examples (e.g., X to Y, orX-Y, where X and Y are values for a particular stimulation parameter,such as amplitude). In addition, or instead, the therapeutic windows canbe displayed as a magnitude of the difference between the efficacythreshold value and the adverse-effects threshold (e.g., a single numberthat indicates the difference between the efficacy threshold value andthe adverse-effects threshold).

As discussed above, the therapeutic windows of electrodes 24, 26 mayprovide a basis for comparing the potential benefits of each of theelectrodes. For example, an electrode associated with a relatively largetherapeutic window may indicate that the electrode will provide morelatitude to find efficacious electrical stimulation parameter values forthe patient than another electrode associated with a relatively smalltherapeutic window. In some examples, the therapeutic windows may bedetermined based on the actual implantation site of leads 20 (e.g., asdiscussed below with respect to FIGS. 4-6) within patient 12, i.e.,post-operatively, such that the information identifying the therapeuticwindows for each of the electrodes 24, 26 may be specifically tailoredto patient 12. As a result, the therapeutic windows may provide a usefulbasis for selecting electrode combinations for programming IMD 16.

In some examples, the therapeutic windows may be determined before leads20 are implanted in patient 12, e.g., pre-operatively. For example, thetherapeutic windows may be determined based on the expected implantationsite of leads 20 in patient 12. In these examples, the therapeuticwindows may be determined based on VTAs determined using images ofpatient 12 (e.g., based on a brain atlas specific to patient 12), suchthat the information identifying the therapeutic windows for each of theelectrodes 24, 26 may be specifically tailored to patient 12. The targetlocation of leads 20 and electrodes 24, 26 may be selected and modeled,e.g., by a processor of programmer 14, in order to determine the VTAsexpected to result from delivery of electrical stimulation by selectelectrode(s) 24, 26 of leads 20 if leads 20 were implanted in patient12. In this way, the therapeutic windows may be used to determine atleast some electrical stimulation parameter values pre-operatively,prior to implantation of leads 20. In addition, programmer 14 (oranother device) may determine the therapeutic windows based on differenttarget locations for electrodes 24, 26, e.g., in order topre-operatively select an actual implant site for leads 20. Processor 14may, for example, select the implant site that results in the relativelylargest therapeutic windows or the relatively greatest number ofelectrodes associated with therapeutic windows greater than or equal toa predetermined size.

Programmer 14 may also be configured for use by patient 12. Whenconfigured as a patient programmer, programmer 14 may have limitedfunctionality (compared to a clinician programmer) in order to preventpatient 12 from altering critical functions of IMD 16 or applicationsthat may be detrimental to patient 12.

Whether programmer 14 is configured for clinician or patient use,programmer 14 is configured to communicate to IMD 16 and, optionally,another computing device, via wireless communication. Programmer 14, forexample, may communicate via wireless communication with IMD 16 usingradio frequency (RF) telemetry techniques known in the art. Programmer14 may also communicate with another programmer or computing device viaa wired or wireless connection using any of a variety of local wirelesscommunication techniques, such as RF communication according to the802.11 or Bluetooth specification sets, infrared (IR) communicationaccording to the IRDA specification set, or other standard orproprietary telemetry protocols. Programmer 14 may also communicate withother programming or computing devices via exchange of removable media,such as magnetic or optical disks, memory cards or memory sticks.Further, programmer 14 may communicate with IMD 16 and anotherprogrammer via remote telemetry techniques known in the art,communicating via a local area network (LAN), wide area network (WAN),public switched telephone network (PSTN), or cellular telephone network,for example.

Therapy system 10 may be implemented to provide chronic stimulationtherapy to patient 12 over the course of several months or years.However, system 10 may also be employed on a trial basis to evaluatetherapy before committing to full implantation. If implementedtemporarily, some components of system 10 may not be implanted withinpatient 12. For example, patient 12 may be fitted with an externalmedical device, such as a trial stimulator, rather than IMD 16. Theexternal medical device may be coupled to percutaneous leads or toimplanted leads via a percutaneous extension. If the trial stimulatorindicates DBS system 10 provides effective treatment to patient 12, theclinician may implant a chronic stimulator within patient 12 forrelatively long-term treatment.

System 10 shown in FIG. 1 is merely one example of a therapy system forwhich a therapeutic window may be determined for one or more electrodes24, 26. The techniques described herein can be used to determine thetherapeutic window of one or more electrodes of other therapy systems,such as therapy systems with other configurations of leads andelectrodes, therapy systems with more than one IMD, and therapy systemsincluding one or more leadless electrical stimulators (e.g.,microstimulators having a smaller form factor than IMD 16 and which maynot be coupled to any separate leads). The leadless electricalstimulators can be configured to generate and deliver electricalstimulation therapy to patient 12 via one or more electrodes on an outerhousing of the electrical stimulator.

During implantation of lead 16 within patient 12, a clinician mayattempt to position electrodes 24, 26 of leads 20 close to or within atarget anatomical region. The anatomical region within patient 12 thatserves as the target tissue site for stimulation delivered by IMD 14 maybe selected based on the patient condition. For example, stimulatingparticular structures of brain 18, such as the Substantia Nigra, mayhelp reduce the number and magnitude of tremors experienced by patient12. Other anatomical regions for DBS may include the subthalamicnucleus, globus pallidus interna, ventral intermediate, and zonainserta.

While DBS may successfully reduce symptoms of some neurologicaldiseases, the stimulation may also cause unwanted side effects, alsoreferred to herein as adverse effects. Side effects may includeincontinence, tingling, loss of balance, paralysis, slurred speech, lossof memory, loss of inhibition, and many other neurological problems.Side effects may be mild to severe. DBS may cause one or more adverseeffects by inadvertently providing electrical stimulation pulses toanatomical regions near the targeted anatomical region. These anatomicalregions may be referred to as regions associated with adversestimulation effects. For this reason, a clinician may program IMD 16with a therapy program (or a plurality of therapy programs) that definesstimulation parameter values that balance effective therapy and minimizeside effects.

With the aid of programmer 14 or another computing device, a clinicianmay select values for therapy parameters for therapy system 10,including an electrode combination. By selecting particular electrodes24, 26 for delivering electrical stimulation therapy to patient 12, aclinician may modify the electrical stimulation therapy to target one ormore particular regions of tissue (e.g., specific anatomical structures)within brain 28 and avoid other regions of tissue within brain 28. Inaddition, by selecting values for the other stimulation parameter valuesthat define the electrical stimulation signal, e.g., the amplitude,pulse width, and pulse rate, the clinician may generate an efficacioustherapy for patient 12 that is delivered via the selected electrodesubset. Due to physiological diversity, condition differences, andinaccuracies in lead placement, the parameter values may vary betweenpatients.

During a programming session, the clinician may determine one or moretherapy programs that may provide effective therapy to patient 12.Patient 12 may provide feedback to the clinician as to the efficacy ofthe specific program being evaluated, which may include informationregarding adverse effects of delivery of therapy according to thespecific program. Once the clinician has identified one or more programsthat may be beneficial to patient 12, patient 12 may continue theevaluation process and determine which program best alleviates thecondition of patient 12 or otherwise provides efficacious therapy topatient 12. Programmer 14 may assist the clinician in thecreation/identification of therapy programs by providing a methodicalsystem of identifying potentially beneficial therapy parameters.

A therapeutic window of a particular electrode 24, 26 may indicatewhether the electrode may be useful for providing efficaciousstimulation therapy to patient 12. Thus, information indicating thetherapeutic window of electrodes 24, 26 may help aid the selection ofone or more electrode combinations that may provide efficaciouselectrical stimulation therapy to patient 12.

In some existing techniques, a clinician may manually determine thetherapeutic window for each electrodes of a therapy system in a unipolarstimulation mode, e.g., during initial programming of the system for apatient. This process may be relatively time consuming. For example, oneelectrode at a time, the clinician may set the IMD can to be the anode,the electrode to be the cathode, and set the pulse width and frequencyof the electrical stimulation to some constant default values. Then, theclinician may systematically increase the amplitude of electricalstimulation in incremental steps to identify the amplitude that firstyields some efficacy for the patient. The clinician may then continueincreasing the amplitude in incremental steps to identify the amplitudethat first yields some undesirable side effects for the patient. Thedifference between these two amplitudes may be the therapeutic windowfor the electrode.

While the therapeutic window information determined using this manualtechnique may be useful, obtaining the therapeutic window information inthis manner can be relatively tedious and time-consuming for theclinician and patient. In addition, the manual process of determiningthe therapeutic window for a plurality of electrodes can fatigue thepatient due to the relatively long duration of time required todetermine the therapeutic window, the frequent delivery of theelectrical stimulation to the patient to determine the therapeuticwindows, or both. If the patient is fatigued, the results of theelectrical stimulation may be adversely impacted, which may decrease theaccuracy of the determined therapeutic windows.

In some examples described herein, a processor of therapy system 10(e.g., a processor of IMD 16 or programmer 14) is configured toautomatically determine the therapeutic windows for electrodes 24, 26based on a VTA expected to result from electrical stimulation deliveredvia the respective electrode in a unipolar configuration. In contrast tothe manual technique of determining therapeutic windows discussed above,the therapeutic windows are determined using computer modeling, ratherthan based on the results of actual electrical stimulation delivered topatient 12 by IMD 16 with the selected stimulation parameter values.Thus, in some examples, the processor may determine the therapeuticwindows without patient 12 being present in a clinic, which may helpreduce the amount of time patient 12 is required to be in the clinic inorder to program IMD 16. In addition, in some examples, therapeuticwindows may be estimated prior to implanting leads 20 in patient 12,which may provide a starting point for programming electricalstimulation parameters for IMD 16 after implanting leads 20 in patient12.

An example technique for determining the therapeutic window for eachelectrode 24, 26 of system 10 is described in further detail below withrespect to FIGS. 4, 7, and 8. For ease of description, the techniquesare primarily described as being employed by programmer 14. In otherexamples, the techniques may be implemented by any suitable device, suchas IMD 16 or another computing device (e.g., a remote computing devicesuch as a cloud computing device), alone or in combination withprogrammer 14.

As described in further detail below, in some examples, programmer 14determines the therapeutic window for each electrode 24, 26 based on avolume of tissue expected to be activated by electrical stimulationdelivered via the respective electrode and a set of electricalstimulation parameter values. Programmer 14 may be configured togenerate the VTA for a particular electrode and a set of electricalstimulation parameter values using any suitable technique, such as anyone of the techniques described below with respect to FIG. 6. In someexamples, a processor of programmer 14 automatically determines thetherapeutic window for a particular electrode by at least determining anefficacy threshold based on the VTA expected to result from the deliveryof electrical stimulation according to a set of electrical stimulationparameter values including the stimulation parameter at the efficacythreshold, and determining the adverse-effects threshold based on theVTA expected to result from the delivery of electrical stimulationaccording to a set of electrical stimulation parameter values includingthe stimulation parameter at the adverse-effects threshold. Thetherapeutic window is defined between the efficacy threshold and theadverse-effects threshold.

For example, the processor may determine a VTA expected to result fromelectrical stimulation delivered by a selected electrode (in a unipolarconfiguration) according to an initial set of electrical stimulationparameters. The processor may then adjust the value (e.g., by increasingor decreasing the value) of at least one electrical stimulationparameter of the set (e.g., one or more of the amplitude, the frequency,the pulse width, and the like) in order to determine the efficacythreshold and the adverse-effects threshold. For example, the processormay incrementally increase the value of an electrical stimulationparameter until the resulting VTA overlaps with one or more efficacyregions of the patient, the efficacy regions being associated withefficacious electrical stimulation. The lowest value at which theresulting VTA overlaps with the one or more efficacy regions may be theefficacy threshold. In addition, the processor may determine theresulting VTA overlaps with one or more efficacy regions of the patientin response to determining the VTA overlaps with the one or moreefficacy regions in an amount sufficient to cause one or moreefficacious effects of electrical stimulation.

In this example, the processor may also determine the lowest value ofthe electrical stimulation parameter at which the resulting VTA overlapswith one or more adverse-effects regions of the patient, the secondregions being associated with adverse effects of electrical stimulation.The lowest value of the electrical stimulation parameter at which theresulting VTA overlaps with the one or more adverse-effects regions maybe the adverse-effects threshold. Again, the processor may determine theresulting VTA overlaps with one or more adverse-effects regions of thepatient in response to determining the VTA overlaps with the one or moreadverse-effects regions in an amount sufficient to cause one or moreadverse effects of electrical stimulation. In addition, by determiningwhich adverse-effects regions of tissue the VTA overlap with, theprocessor may also be able to determine which side effects may resultfrom the delivery of electrical stimulation via the electrode.

The electrical stimulation parameter value at which the VTA overlapswith the one or more adverse-effects regions may be higher than thelowest electrical stimulation parameter value at which a VTA overlapswith the one or more efficacy regions. The processor may then determinethe therapeutic window based on the efficacy threshold and theadverse-effects threshold, e.g., the processor may define thetherapeutic window as being bounded by the efficacy threshold and theadverse-effects threshold or as having a magnitude substantially equal(e.g., equal or nearly equal) to the difference between the efficacythreshold and the adverse-effects threshold.

In other examples, depending on the electrical stimulation parameterwith which the therapeutic window is defined, the highest value at whichthe resulting VTA overlaps with the one or more efficacy regions may bethe efficacy threshold and the highest value of the electricalstimulation parameter at which the resulting VTA overlaps with the oneor more adverse-effects regions may be the adverse-effects threshold. Inthese examples, the electrical stimulation parameter value at which theVTA overlaps with the one or more adverse-effects regions may be lowerthan the lowest electrical stimulation parameter value at which a VTAoverlaps with the one or more efficacy regions.

After determining the therapeutic windows for each electrode 24, 26, theprocessor of programmer 14 may store the therapeutic windows with anindication of the associated electrode, generate and present a displaythat includes a list of a plurality of electrodes and respectivetherapeutic windows, or any combination thereof.

FIG. 2 is functional block diagram illustrating components of an exampleIMD 16. In the example shown in FIG. 2, IMD 16 includes processor 60,memory 62, stimulation generator 64, sensing module 66, switch module68, telemetry module 70, and power source 72. Memory 62, as well asother memories described herein, may include any volatile ornon-volatile media, such as a random access memory (RAM), read onlymemory (ROM), non-volatile RAM (NVRAM), electrically erasableprogrammable ROM (EEPROM), flash memory, and the like. Memory 62 maystore computer-readable instructions that, when executed by processor60, cause IMD 16 to perform various functions described herein.

In the example shown in FIG. 2, memory 62 stores therapy programs 74 andoperating instructions 76, e.g., in separate memories within memory 62or separate areas within memory 62. Each stored therapy program 74defines a particular program of therapy in terms of respective valuesfor electrical stimulation parameters, such as an electrode combination,current or voltage amplitude, and, if stimulation generator 64 generatesand delivers stimulation pulses, the therapy programs may define valuesfor a pulse width, and pulse rate of a stimulation signal. Each storedtherapy program 74 may also be referred to as a set of therapy parametervalues. Operating instructions 76 guide general operation of IMD 16under control of processor 60, and may include instructions formonitoring brain signals within one or more brain regions via electrodes24, 26 and delivering electrical stimulation therapy to patient 12.

Stimulation generator 64, under the control of processor 60, generatesstimulation signals for delivery to patient 12 via selected combinationsof electrodes 24, 26. In some examples, stimulation generator 64generates and delivers stimulation signals to one or more target regionsof brain 28 (FIG. 1), via a select combination of electrodes 24, 26,based on one or more stored therapy programs 74. The target tissue siteswithin brain 28 for stimulation signals or other types of therapy andstimulation parameter values may depend on the patient condition forwhich therapy system 10 is implemented to manage. While stimulationpulses are described, stimulation signals may be of any form, such ascontinuous-time signals (e.g., sine waves) or the like.

The processors described in this disclosure, including processor 60, mayinclude one or more digital signal processors (DSPs), general purposemicroprocessors, application specific integrated circuits (ASICs), fieldprogrammable logic arrays (FPGAs), or other equivalent integrated ordiscrete logic circuitry, or combinations thereof. The functionsattributed to processors described herein may be provided by a hardwaredevice and embodied as software, firmware, hardware, or any combinationthereof. Processor 60 is configured to control stimulation generator 64according to therapy programs 74 stored by memory 62 to apply particularstimulation parameter values specified by one or more programs, such asamplitude, pulse width, and pulse rate.

In the example shown in FIG. 2, the set of electrodes 24 of lead 20Aincludes electrodes 24A, 24B, 24C, and 24D, and the set of electrodes 26of lead 20B includes electrodes 26A, 26B, 26C, and 26D. Processor 60 maycontrol switch module 68 to apply the stimulation signals generated bystimulation generator 64 to selected combinations of electrodes 24, 26.In particular, switch module 68 may couple stimulation signals toselected conductors within leads 20, which, in turn, deliver thestimulation signals across selected electrodes 24, 26. Switch module 68may be a switch array, switch matrix, multiplexer, or any other type ofswitching module configured to selectively couple stimulation energy toselected electrodes 24, 26 and to selectively sense bioelectrical brainsignals with selected electrodes 24, 26. Hence, stimulation generator 64is coupled to electrodes 24, 26 via switch module 68 and conductorswithin leads 20. In some examples, however, IMD 16 does not includeswitch module 68.

Stimulation generator 64 may be a single channel or multi-channelstimulation generator. In particular, stimulation generator 64 may becapable of delivering a single stimulation pulse, multiple stimulationpulses or continuous signal at a given time via a single electrodecombination or multiple stimulation pulses at a given time via multipleelectrode combinations. In some examples, however, stimulation generator64 and switch module 68 may be configured to deliver multiple channelson a time-interleaved basis. For example, switch module 68 may serve totime divide the output of stimulation generator 64 across differentelectrode combinations at different times to deliver multiple programsor channels of stimulation energy to patient 12.

Sensing module 66, under the control of processor 60, is configured tosense bioelectrical brain signals of patient 12 via a selected subset ofelectrodes 24, 26 or with one or more electrodes 24, 26 and at least aportion of a conductive outer housing 34 of IMD 16, an electrode on anouter housing of IMD 16 or another reference. Processor 60 may controlswitch module 68 to electrically connect sensing module 66 to selectedelectrodes 24, 26. In this way, sensing module 66 may selectively sensebioelectrical brain signals with different combinations of electrodes24, 26 (and/or a reference other than an electrode 24, 26).

Although sensing module 66 is incorporated into a common housing 34 withstimulation generator 64 and processor 60 in FIG. 2, in other examples,sensing module 66 is in a separate outer housing from outer housing 34of IMD 16 and communicates with processor 60 via wired or wirelesscommunication techniques.

Telemetry module 70 is configured to support wireless communicationbetween IMD 16 and an external programmer 14 or another computing deviceunder the control of processor 60. Processor 60 of IMD 16 may receive,as updates to programs, values for various stimulation parameters suchas amplitude and electrode combination, from programmer 14 via telemetrymodule 70. The updates to the therapy programs may be stored withintherapy programs 74 portion of memory 62. Telemetry module 70 in IMD 16,as well as telemetry modules in other devices and systems describedherein, such as programmer 14, may accomplish communication by RFcommunication techniques. In addition, telemetry module 70 maycommunicate with external medical device programmer 14 via proximalinductive interaction of IMD 16 with programmer 14. Accordingly,telemetry module 70 may send information to external programmer 14 on acontinuous basis, at periodic intervals, or upon request from IMD 16 orprogrammer 14.

Power source 72 delivers operating power to various components of IMD16. Power source 72 may include a small rechargeable or non-rechargeablebattery and a power generation circuit to produce the operating power.Recharging may be accomplished through proximal inductive interactionbetween an external charger and an inductive charging coil within IMD16. In some examples, power requirements may be small enough to allowIMD 16 to utilize patient motion and implement a kineticenergy-scavenging device to trickle charge a rechargeable battery. Inother examples, traditional batteries may be used for a limited periodof time.

FIG. 3 is a functional block diagram illustrating components of anexample medical device programmer 14 (FIG. 1). Programmer 14 includesprocessor 80, memory 82, telemetry module 84, user interface 86, andpower source 88. Processor 80 controls user interface 86 and telemetrymodule 84, and stores and retrieves information and instructions to andfrom memory 82. Programmer 14 may be configured for use as a clinicianprogrammer or a patient programmer. Processor 80 may comprise anycombination of one or more processors including one or moremicroprocessors, DSPs, ASICs, FPGAs, or other equivalent integrated ordiscrete logic circuitry. Accordingly, processor 80 may include anysuitable structure, whether in hardware, software, firmware, or anycombination thereof, to perform the functions ascribed herein toprocessor 80.

A user, such as a clinician or patient 12, may interact with programmer14 through user interface 86. User interface 86 includes a display (notshown), such as a LCD or LED display or other type of screen, with whichprocessor 80 may present information related to the therapy (e.g.,electrodes and associated therapeutic windows). In addition, userinterface 86 may include an input mechanism to receive input from theuser. The input mechanisms may include, for example, any one or more ofbuttons, a keypad (e.g., an alphanumeric keypad), a peripheral pointingdevice, a touch screen, or another input mechanism that allows the userto navigate though user interfaces presented by processor 80 ofprogrammer 14 and provide input. In other examples, user interface 86also includes audio circuitry for providing audible notifications,instructions or other sounds to patient 12, receiving voice commandsfrom patient 12, or both.

Memory 82 may include instructions for operating user interface 86 andtelemetry module 84, and for managing power source 88. In the exampleshown in FIG. 3, memory 82 also stores regions 90, patient anatomy data92, therapy programs 94, VTA algorithms 96, and therapeutic windowinformation 98.

Regions 90 stores information identifying one or more regions of tissueof brain 28 (or another part of the body of the patient) associated withefficacious therapy delivery. These regions may be referred to asefficacy regions. Regions 90 also stores information identifying one ormore regions of tissue of brain 28 (or another part of the body ofpatient) associated with adverse stimulation effects. These regions maybe referred to as adverse-effects regions. The regions 90 may beidentified using any suitable convention. In some examples, the efficacyand adverse-effects regions are identified by specific brain structuresor parts of brain structures, coordinates of any suitable coordinatesystem to which leads 20 and brain 28 are registered, other anatomicalstructures, pixels of a two-dimensional (2D) grid to which brain 28 oranother portion of the body of patient 12 is registered, voxels of athree-dimensional (3D) grid to which brain 28 or another portion of thebody of patient 12 is registered (as discussed in further detail below),or any combination thereof.

The efficacy regions and adverse-effects regions stored by regions 90may differ depending on the patient condition. For example, if therapysystem 10 is implemented to manage tremors experienced by patient 12,regions 90 may include the substantia nigra because for some patients,stimulating the substantia nigra, may help reduce the number andmagnitude of tremors experienced by the patient.

In some examples, a clinician selects the stored regions 90. In otherexamples, the regions 90 are preselected and associated with a patientcondition; processor 80 or a clinician may determine the regions 90relevant to patient 12 by selecting the patient condition for whichsystem 10 is implemented to manage.

Processor 80 is configured to generate a VTA for a particular set ofstimulation parameter values, where the VTA represents the volume oftissue of patient 12 expected to be activated by the delivery, by aparticular electrode (or combination of electrodes), of electricalstimulation to tissue of patient 12 according to the set of stimulationparameters. Processor 80 is configured to generate, for a particularelectrode and a set of electrical stimulation parameter values, a VTAusing VTA algorithms 96 and patient anatomy data 92 stored by memory 82to generate the VTA. Patient anatomy data 92 may, for example, includethe location of implanted electrodes 24, 26 in brain 28, the anatomicalstructure of patient 12, and the characteristics of the tissue, such asthe impedance, proximate to implanted electrodes 24, 26. In examples inwhich the therapeutic windows (or just the efficacy and adverse-effectsthresholds) are determined before leads 20 are implanted in patient 12,patient anatomy data 92 may not include the actual location of implantedelectrodes 24, 26 in brain 28, but, rather, a target location forelectrodes 24, 26 in brain 28. Patient anatomy data 92 may be createdfrom any type of imaging modality, such as, but not limited to, computedtomography (CT), magnetic resonance imaging (MM), x-ray, fluoroscopy,and the like.

VTA algorithms 96 may include one or more algorithms that processor 80may implement to generate a VTA for a particular set of electricalstimulation parameter values and one or more active electrodes. When IMD16 delivers electrical stimulation to tissue of patient 12 via anelectrode (or combination of electrodes), an electrical field propagatesaway from the electrode. Processor 80 can implement the algorithms 96 toestimate which neurons will be activated by the electrical fieldpropagating away from an electrode 24, 26 during the delivery ofelectrical stimulation by the electrode.

In some examples, the VTA algorithms 96 may include, for example,electrical field model equations that define how an electrical fieldpropagates away from an origin location. In addition, VTA algorithms 96may also include a set of equations, a lookup table, or another type ofmodel that defines threshold action potentials of particular neuronsthat make up the anatomical structure, as defined by the patient anatomydata, affected by an electrical field. If the voltage or currentamplitude of the electrical field is above the threshold actionpotential of any neuron within the electrical field, that neuron will beactivated, e.g., cause a nerve impulse. Due to changes in electricalcurrent propagation and threshold action potentials (e.g., a thresholdvoltage) required to activate a neuron, the activation of neurons mayvary with the location of tissue around the lead. Some neurons mayactivate further from the lead with smaller voltages while other neuronsmay only be activated close to the lead because of a high voltagethreshold.

In some examples, memory 82 also stores information regarding thehardware characteristics of leads 20 and processor 80 generates the VTAbased on the hardware characteristics. The hardware characteristics mayinclude, for example, the number or types of leads 20 implanted withinpatient 12, the number of electrodes 24, 26, the size of each of theelectrodes 324, 26, the type of electrodes 24, 26 (e.g., ringelectrodes, partial-ring electrodes, segmented electrodes), and thelike.

In some examples, processor 80 is configured to store determinedtherapeutic windows and associated electrodes in memory 82 astherapeutic window information 98. A clinician may review the storedinformation 98, e.g., during programming of IMD 16 to select one or moreelectrode combinations with which IMD 16 may deliver efficaciouselectrical stimulation to patient 12. For example, the clinician mayinteract with user interface 86 to retrieve the stored therapeuticwindow information 96. In some examples, processor 80 is configured togenerate and display a graphical user interface that indicates, for atleast one electrode 24, 26 (e.g., each electrode 24, 26 or at least twoelectrodes 24, 26), the respective therapeutic window. The clinician maythen ascertain, relatively quickly, from the displayed information whichelectrodes have the largest therapeutic window, which may be theelectrodes associated with the most latitude to find electricalstimulation parameter values that provide efficacious electricalstimulation therapy for patient 12.

In some examples, the clinician (or another user) may provide input viauser interface 86 to manipulate the therapeutic window information. Forexample, in response to receiving user input requesting the list ofelectrodes be ordered by therapeutic window, efficacy threshold, oradverse-effects threshold, processor 80 may reorganize the list ofelectrodes based on the size of the associated therapeutic window,efficacy threshold, or adverse-effects threshold, respectively (e.g.,from large to small or vice versa).

Processor 80 may be configured to generate other types of interfaces.For example, processor 80 may be configured to generate a displayincluding a list of electrodes (e.g., each electrode may be assigned aunique alphanumeric identifier or a graphical identifier) ordered basedon the associated therapeutic windows, efficacy thresholds, oradverse-effects threshold without displaying the therapeutic windows,efficacy thresholds, or adverse-effects threshold, respectively. Theclinician may then provide input via user interface 86 requestingadditional information about a particular electrode. In response toreceiving the user input, processor 80 may present another userinterface with further details about the selected electrode, such as theone or more of the associated therapeutic window, efficacy threshold, oradverse-effects threshold.

In some examples, patient 12, a clinician or another user may interactwith user interface 86 of programmer 14 in other ways to manually selecttherapy programs, generate new therapy programs, modify therapyprograms, transmit the new programs to IMD 16, or any combinationthereof.

Memory 82 may include any volatile or nonvolatile memory, such as RAM,ROM, EEPROM or flash memory. Memory 82 may also include a removablememory portion that may be used to provide memory updates or increasesin memory capacities. A removable memory may also allow sensitivepatient data to be removed before programmer 14 is used by a differentpatient.

Wireless telemetry in programmer 14 may be accomplished by RFcommunication or proximal inductive interaction of external programmer14 with IMD 16. This wireless communication is possible through the useof telemetry module 84. Accordingly, telemetry module 84 may be similarto the telemetry module contained within IMD 16. In other examples,programmer 14 may be capable of infrared communication or directcommunication through a wired connection. In this manner, other externaldevices may be capable of communicating with programmer 14 withoutneeding to establish a secure wireless connection.

Power source 88 is configured to deliver operating power to thecomponents of programmer 14. Power source 88 may include a battery and apower generation circuit to produce the operating power. In someexamples, the battery may be rechargeable to allow extended operation.Recharging may be accomplished by electrically coupling power source 88to a cradle or plug that is connected to an alternating current (AC)outlet. In addition, recharging may be accomplished through proximalinductive interaction between an external charger and an inductivecharging coil within programmer 14. In other examples, traditionalbatteries (e.g., nickel cadmium or lithium ion batteries) may be used.In addition, programmer 14 may be directly coupled to an alternatingcurrent outlet to operate.

FIG. 4 is a flow diagram illustrating an example technique fordetermining a therapeutic window for at least one electrode of a therapysystem. While the techniques shown in FIGS. 4-8 are primarily describedas being performed by processor 80 of programmer 14, in other examples,a processor of another device, such as processor 60 of IMD 16, canperform any part of the techniques shown in FIGS. 4-8, alone or incombination with processor 80. In addition, while the techniques shownin FIGS. 4, 7, and 8 are described with respect to determining thetherapeutic window for each electrode 24, 26 of a plurality ofelectrodes 24, 26 of system 10, in other examples, the techniques shownin FIGS. 4, 7, and 8 can be used to determine the therapeutic window forany number of electrodes, such as only one electrode, only a subset ofelectrodes of system 10, or all of the electrodes of system 10.

A therapeutic window may be specifically associated with a singleelectrode or a subset of electrodes (e.g., a specific electrodecombination) because the efficacy threshold and adverse-effectsthreshold depends upon the results (or expected results) of theelectrical stimulation delivered by IMD 16 with the electrode or subsetof electrodes. In the example technique shown in FIG. 4 (as well asFIGS. 7 and 8), processor 80 determines the therapeutic window for anelectrode based on a VTA resulting from electrical stimulation deliveredvia the electrode in a unipolar configuration, e.g., using the housingof IMD 16 as a reference. In other examples, processor 80 may, accordingto the techniques shown in FIGS. 4, 7, and 8, determine the therapeuticwindow for an electrode combination (e.g., for bipolar electricalstimulation).

In the technique shown in FIG. 4, processor 80 selects an electrode(100) for which a therapeutic window will be determined. Processor 80may select the electrode from a plurality of electrodes 24, 26.

A therapeutic window may be defined by a range of values of any suitableelectrical stimulation parameter that may affect the results (boththerapeutic and adverse) of electrical stimulation delivered by IMD 16.In the example shown in FIG. 4, the therapeutic window determined byprocessor 80 is defined by a range of stimulation amplitude values (alsoreferred to herein as “amplitude” values). The amplitude values indicatethe amplitude of the electrical stimulation signal delivered by IMD 16,and may be voltage amplitude values or current amplitude values, e.g.,depending on whether IMD 16 is a voltage controlled device or a currentcontrolled device. In other examples, however, the therapeutic windowmay be defined by another type of electrical stimulation parameter, suchas, but not limited to, a frequency or pulse width.

Processor 80 may select an initial amplitude value (102). In someexamples, memory 82 of programmer 14 stores a predetermined maximumamplitude value (or other stimulation parameter value), and processor 80selects the initial amplitude value to be less than the predeterminedmaximum. The predetermined maximum can be, for example, a stimulationamplitude value that is known to be higher than an expected efficacythreshold value. The initial amplitude value may be a part of an initialset of electrical stimulation parameter values that processor 80 selectsin order to start the determination of the therapeutic window for anelectrode. In some examples, the initial set of electrical stimulationparameter values includes values for a pulse width, a frequency, and anamplitude of electrical stimulation. The pulse width and frequency mayremain fixed at the values of the initial set of electrical stimulationparameter values, while processor 80 may adjust the amplitude from theinitial amplitude value in order to determine the therapeutic window.The initial amplitude value can be one that is expected (e.g., based onpast clinician experience or based on computer modeling) to be less thanthe efficacy threshold for patient 12 when electrical stimulation isdelivered via the selected electrode. The efficacy threshold may be thelowest amplitude value at which efficacious results of electricalstimulation may be observed.

If processor 80 determines the therapeutic window for a plurality ofelectrodes, processor 80 may start each therapeutic window determinationwith the initial set of electrical stimulation parameter values, or atleast with substantially the same (e.g., the same or nearly the same)values of the electrical stimulation parameters that remain fixed duringthe therapeutic window determination. In this way, the values of theelectrical stimulation parameters that remain fixed during thetherapeutic window determination are substantially the same for all theelectrodes, which may help aid the comparison of the therapeutic windowsto each other.

Processor 80 determines the VTA based on the selected amplitude value(104), where the VTA indicates the volume of tissue that is expected(e.g., estimated) to be activated by the stimulation field resultingfrom delivery of electrical stimulation by IMD 16 via the selectedelectrode (in a unipolar configuration), the electrical stimulationbeing generated by IMD 16 in accordance with the selected stimulationamplitude value and the other stimulation parameter values of theinitial set. Processor 80 can determine the VTA using any suitabletechnique, such as the example technique described with respect to FIG.6. As described with respect to FIG. 6, in some examples, processor 80utilizes an algorithm (e.g., stored as a VTA algorithm 96 in memory 82of programmer 14) to determine an electrical field that indicates thestimulation field that will propagate away from the electrode when asignal stimulation signal initial set of stimulation parameter values isdelivered by the electrode. Based on the electrical field and patientanatomy data 92 (e.g., one or more impedance characteristics of patientneural tissue proximate the selected electrode), processor 80 mayestimate the volume of tissue of brain 28 (or other tissue areas) thatwill be activated by the electrical field.

Example techniques that processor 80 may use to determine a VTA (104)are described in commonly-assigned U.S. Pat. No. 7,822,483 to Stone etal., entitled, “ELECTRICAL AND ACTIVATION FIELD MODELS FOR CONFIGURINGSTIMULATION THERAPY” and issued on Oct. 26, 2010, and commonly-assignedU.S. Patent Application Publication No. 2013/0289380 by Molnar et al.,entitled, “VISUALIZING TISSUE ACTIVATED BY ELECTRICAL STIMULATION,” andfiled on Mar. 14, 2013. The entire content of U.S. Pat. No. 7,822,483 toStone et al. and U.S. Patent Application Publication No. 2013/0289380 byMolnar et al. is hereby incorporated by reference.

In accordance with some examples described in U.S. Patent ApplicationPublication No. 2013/0289380 by Molnar et al., a volume of activation oftissue resulting from delivery of electrical stimulation according to aset of stimulation parameter values may be determined based on a uniformor non-uniform grid of neuron representatives that indicate the neuronsof the tissue of the patient proximate electrodes 24, 26. Each neuronrepresentative may be associated with a threshold value of activation(also referred to herein as an “activation threshold value” or“activation threshold”). The threshold value for each neuronrepresentative may be obtained using a binary search algorithm. Thethreshold value is a stimulation voltage or current amplitude, that whenapplied to an actual neuron of the type being modeled by processor 80,results in a propagating action potential along the neuron. In someexamples, the action potential is considered to have excited, or“activated,” the neuron representative if the transmembrane potentialreached a threshold greater than 0 mV. As used herein, the thresholdvalue of activation may be referred to as a threshold, an activationthreshold, or a propagation threshold.

After generating the VTA (104), processor 80 determines whether the VTAoverlaps with one or more first regions of tissue (106). In the exampleshown in FIG. 4, the one or more first regions of tissue are efficacyregions of brain 28, which is a region of brain tissue associated withefficacious therapy delivery when the tissue (e.g., a sufficient amountof tissue) in the region is activated. As discussed above with respectto FIG. 3, in some examples, information defining or otherwiseidentifying the first region may be stored in memory 82 of programmer14, as part of regions 90.

Processor 80 can determine whether the VTA overlaps with the one or morefirst regions of tissue (106) using any suitable technique. In someexamples, processor 80 determines whether the coordinates of theperimeter of the VTA overlap with the coordinates of the one or morefirst regions, the coordinates being stored by memory 82. In addition,or instead, if one or more first regions are defined by an anatomicalstructure of brain 28, processor 80 may determine whether thecoordinates of the perimeter of the VTA fall within the anatomicalstructure in order to determine whether the VTA overlaps with the one ormore first regions. In another example, processor 80 determines whetherthe VTA overlaps with the one or more first regions of tissue (106)using the technique described with respect to FIG. 5, in which processor80 registers the VTA and one or more first regions to a 3D grid ofvoxels, and determines the overlap based on the voxels lying in both theVTA and the one or more first regions.

In response to determining the VTA does not overlap with the one or morefirst regions (“NO” branch of block 106), processor 80 increases theamplitude by a predetermined increment (108), and then determines theVTA resulting from the modified amplitude (104). The predeterminedincrement may be stored by memory 82 of programmer 14 (or a memory ofanother device). The predetermined increment may be selected using anysuitable criteria. In some examples, the size of the increment by whichthe stimulation amplitude (or other parameter) is adjusted may beselected to be large enough to result in a change to the VTA, but smallenough to provide a gradual change in size to the VTA. For example, thesize of the increment by which processor 80 may adjust the stimulationamplitude may be 0.1 millivolts, 0.2 millivolts, 0.3 millivolts, 0.4millivolts, or 0.5 millivolts, although other increments can be used inother examples. The gradual change may enable processor 80 to modify thesize of the VTA to be adjusted with small enough granularity to enable arelatively accurate determination of the boundaries of the therapeuticwindow.

Processor 80 may continue increasing the amplitude by the predeterminedincrement (108) and determining the VTA (104) until the determined VTAoverlaps with the one or more first regions of brain 28 (“YES” branch ofblock 106). In response to determining the VTA generated based on aparticular stimulation amplitude value overlaps with the one or morefirst regions of brain 28 (“YES” branch of block 106), processor 80selects the amplitude value as the first threshold value (110). Inexamples in which the one or more first regions are associated withefficacious results of electrical stimulation, the first threshold valuemay be an efficacy threshold for the selected electrode.

Processor 80 may continue increasing the amplitude by a predeterminedincrement (relative to the first threshold value) (112) and determiningthe VTA based on the amplitude value (114) until processor 80 determinesthe VTA overlaps with one or more second regions of tissue (“YES” branchof block 116). The predetermined increment with which the amplitude isincreased from the first threshold value may be the same as, ordifferent than, the predetermined increment with which processor 80increased the amplitude (108) in order to determine the first thresholdvalue.

The one or more second regions may each be a region of tissue of patient12 associated with adverse stimulation effects. In the example shown inFIG. 4, one or more second regions are regions of brain 28. As with theone or more first regions, information defining or otherwise identifyingthe one or more second regions may be stored by memory 82 (FIG. 3) ofprogrammer 14, as part of region 90.

Processor 80 may determine whether the VTA overlaps with one or moresecond regions of brain 28 (116) using any suitable technique, such asany of those described above with respect to determining whether a VTAoverlaps with the one or more first regions (106). In response todetermining the VTA generated based on a particular stimulationamplitude value overlaps with the one or more second regions of brain 28(“YES” branch of block 116), processor 80 selects the amplitude value asthe second threshold value (118). In examples in which the one or moresecond regions are associated with adverse effects of electricalstimulation, the second threshold value may be an adverse-effectsthreshold for the selected electrode.

Processor 80 determines the therapeutic window for the electrode basedon the determined first and second threshold values (120). In someexamples, the therapeutic window is bounded by the first and secondthreshold values. The therapeutic window may include the first thresholdvalue, but not the second threshold value in some examples. In someexamples, processor 80 may associate the determined therapeutic windowwith the electrode and store the electrode and associated therapeuticwindow in memory 82 of programmer 14 or a memory of another device. Inaddition, in some examples, processor 80 may store, in memory 82, thefirst threshold as a predicted efficacy threshold for patient 12 and thesecond threshold as an adverse-effects threshold for patient 12, andassociate the efficacy and adverse-effects thresholds with the electrodein memory 82.

Using the technique shown in FIG. 4, processor 80 may determine theefficacy threshold and adverse-effects threshold and the therapeuticwindow for each electrode of a plurality of electrodes based on anexpected effect of the electrical stimulation, and in the absence of theactual delivery of electrical stimulation to patient 12 via theelectrodes, as in the manual technique described above. As a result, aclinician may, using programmer 14, determine the efficacy andadverse-effects thresholds and the therapeutic windows for theelectrodes 24, 26 of leads 20 (or just a subset of electrodes 24, 26) inadvance of a programming session with patient 12. This may help reducethe amount of time patient 12 is in the clinic to program efficacioustherapy programs for IMD 16.

The clinician may, in some examples, confirm one or more of the efficacyand adverse-effects thresholds and the therapeutic windows automaticallydetermined by processor 80. For example, the clinician may, usingprogrammer 14 or another device, control IMD 16 to deliver electricalstimulation to patient 12 via a selected electrode with a set ofelectrical stimulation parameter values, and then increase the amplitudevalue while maintaining the other electrical stimulation parameters atrelatively constant values. The clinician may then determine, based onpatient input or based on the input of one or more sensors thatindicates the effects of electrical stimulation, a first amplitude valueat which therapeutic effects of stimulation were first observed, and asecond amplitude value at which adverse effects of stimulation werefirst observed. Processor 80, or the clinician, may compare the firstamplitude value to the efficacy threshold associated with the selectedelectrode in memory 82 and compare the second amplitude value to theadverse-effects threshold associated with the selected electrode. Inresponse to determining the first amplitude value and the efficacythreshold are substantially the same (e.g., differ by no more than theamount of the predetermined increment used by the processor 80),processor 80 may confirm the efficacy threshold. In response todetermining the second amplitude value and the adverse-effects thresholdare substantially the same (e.g., differ by no more than the amount ofthe predetermined increment 108 used by the processor 80), processor 80may confirm the adverse-effects threshold.

In the technique shown in FIG. 4, whether or not the value of a selectedstimulation parameter value is increased or decreased in order todetermine the first and second threshold values may depend on whetherthe first or second threshold values are determined first, the type ofstimulation parameter used to define the thresholds, or any combinationthereof. For example, in other examples of the technique shown in FIG.4, instead increasing the amplitude (108, 112) to determine the firstand second threshold values, processor 80 may select a relatively highstimulation amplitude value (102) and decrease the amplitude inpredetermined increments in order determine the first and secondthreshold values. In these examples, processor 80 may determine thesecond threshold prior to determining the second threshold.

While FIG. 4 illustrates a technique in which processor 80 determinesthe therapeutic window for a selected electrode by modifying the valueof only one electrical stimulation parameter value and holding the otherelectrical stimulation parameter values constant, in other examples,processor 80 may determine the therapeutic window for a selectedelectrode by modifying the value of more than one electrical stimulationparameter value. In these examples, the therapeutic window may bedefined by multiple electrical stimulation parameters.

Processor 80 may determine whether a VTA sufficiently overlaps with oneor more particular regions of brain 28 (106, 116) or another region oftissue within patient 12 using any suitable technique. The overlappingportions of a VTA and the one or more regions of space may cover thesame space (e.g., a volume). In some examples, processor 80 maydetermine there is overlap between a VTA and the first or second regionsin response to determining the amount of commonality in 3D space betweenthe VTA and respective region of tissue may be sufficient to produce anefficacious result or an adverse result, respectively. Processor 80 mayuse the technique shown in FIG. 5 to assess the amount of commonality in3D space between the VTA and respective region of tissue. In someexamples, the commonality of space that constitutes an overlap differsdepending on whether processor 80 is determining the efficacy thresholdor the adverse-effects threshold. In other examples, the commonality ofspace that constitutes an overlap is the same for the purposes ofdetermining both the efficacy threshold and the adverse-effectsthreshold.

FIG. 5 is a flow diagram of an example technique that processor 80 mayimplement in order to determine whether a VTA overlaps with one or moreparticular regions of tissue. The technique shown in FIG. 5 may also beused to determine whether a VTA overlaps with one or more regions oftissue outside of brain 28, such as one or more regions of tissueproximate one or more nerves.

In some examples, processor 80 registers the VTA and the region of brain28 to each other, such that the VTA and the region are properlypositioned and sized relative to each other in 3D space. In the exampleshown in FIG. 5, processor 80 registers the VTA to a 3D grid of voxels,which are units of volume and a region of tissue is defined by specificvoxels of the 3D grid. A voxel is a volume element with which the 3Dgrid may be constructed. Every point within the space represented by the3D grid is within one and only one voxel, such that the space is filledby non-overlapping voxels. The voxels of the 3D grid may besubstantially the same size in some examples, but can be different sizesin other examples. The voxels of the 3D grid may have any suitable size.While a relatively small size may be useful for fine tuning thedetermination of both the efficacy and adverse-effects threshold, arelatively small size voxel may also increase the processing timeconsumed by processor 80 to determine whether a VTA overlaps with one ormore particular regions of tissue of patient 12. In some examples, eachvoxel of the 3D grid is about one cubic millimeter (mm³).

Processor 80 may register the VTA to a 3D grid using any suitabletechnique, such as by registering the VTA to the 3D grid based on theknown locations of leads 20 in brain 28, based on known locations of oneor more anatomical structures of brain 28, or both. Other registrationtechniques may also be used. For example, the VTA may be computed with3D coordinates relative to the locations of electrodes 24 or 26 of leads20 and then translated and rotated in three dimensions to coordinatesrelative to the anatomical structures of the brain 28 based on knowledgeof the location of the lead 20 in brain 28.

After determining the VTA, e.g., using the technique described withrespect to FIG. 6, processor 80 determines the voxels common to the VTAand the one or more regions of tissue (e.g., the first regions or thesecond regions discussed above with respect to FIG. 4) (130). Forexample, processor 80 may determine the voxels of the 3D grid that sitwithin both the VTA and the one or more regions of tissue in order todetermine the voxels common to the VTA and the one or more region oftissue. For this determination, for example, processor 80 may determinea voxel of the 3D grid to be within or not within the VTA, and within ornot within a region of tissue, based on whether the coordinates of thecentroid of the voxel are within the VTA or within the region of tissue,respectively. The centroid of the voxel is that point in space that isthe geometric center of the voxel, e.g., as defined in mathematics forconvex n-dimensional polyhedra.

A voxel may only be common to the VTA and one region of tissue. Thus, ifprocessor 80 is determining whether there is overlap between the VTA andmultiple regions of tissue, processor 80 may, in some examples,determine the voxels common to the VTA and at least one of the regionsof tissue.

Processor 80 determines a score based on the voxels in common (132). Thescore may represent the extent to which the VTA extends within the oneor more regions of tissue and, in some examples, may also representwhether the VTA overlaps with the one or more regions of tissue in amanner that may physiologically affect patient 12. For example, in thecase of one or more efficacy regions, the score may indicate whether theextent to which the VTA extends within the one or more efficacy regionswill result in efficacious therapy delivery to patient 12. In the caseof one or more adverse-effects regions, the score may indicate whetherthe extent to which the VTA extends within the one or moreadverse-effects regions will result in one or more adverse effects.

In some examples in which a region of tissue is defined by a pluralityof voxels of a 3D grid and processor 80 registers the VTA to the 3Dgrid, each voxel of the 3D grid may be assigned a value. In theseexamples, processor 80 may determine the score (132) based on a sum ofthe values assigned to each voxel common to the VTA and the region oftissue. If processor 80 is determining whether there is overlap betweenthe VTA and multiple regions of tissue, processor 80 may, in someexamples, combine the values of the voxels common to the VTA and atleast one of the regions of tissue. In this way, the multiple regionscan be treated as a single region, even if the multiple regions are notdirectly adjacent to each other in patient 12. The voxel values may bedetermined by processor 80 of programmer 14 or a processor of anotherdevice prior to the determination of the therapeutic window. In someexamples, 3D grid and voxel values may be stored by memory 82 ofprogrammer 14 or a memory of another device.

The value of a particular voxel may change based on the patientcondition. For example, for one patient condition, a particular voxelmay be associated with a relatively high value, while for anotherpatient condition, the same voxel may be associated with a relativelylow value. In some examples, processor 80 selects the 3D grid frommemory 82 (FIG. 3) or a memory of another device based on a patientcondition of patient 12 for which system 10 is implemented to treat. Inother examples, memory 82 only stores the 3D grid relevant to thepatient condition for which system 10 is implemented to treat andprocessor 80 retrieves the 3D grid from memory 82 without having toselect the grid from a plurality of grids based on the patientcondition. In either example, the values of the voxels may be specificto a patient condition.

The voxel values may be determined based on neuroscience principles, orderived from the cumulative past experience with other patients who havereceived the same type of therapy. For example, processor 80 (or aprocessor of another device) may assign each voxel a value based onknowledge that activation of tissue within the particular voxel resultedin efficacious electrical stimulation to patient 12 or a group ofpatients having the same or similar patient conditions, where the groupmay or may not include patient 12. As an example, if electricalstimulation of a particular structure within brain 28 (e.g., thesubthalamic nucleus) is known to provide therapeutic benefits to apatient having a particular patient condition, processor 80 may assigneach voxel within the particular structure a relatively high value(e.g., a 3 on a scale of 0-3).

In the case of Parkinson's disease, for example, electrical stimulationof the subthalamic nucleus may provide efficacious results. Thus,processor 80 may assign each voxel with a centroid that sits within thesubthalamic nucleus a relatively high value (e.g., a 3 on a scale of0-3). In another example, processor 80 may assign each voxel with acentroid that sits within the border between the subthalamic nucleus andadjacent structures a lower value (e.g., a 2 on a scale of 0-3) than thevalues assigned to the voxels that are more internal to the subthalamicnucleus. This convention may also be used with other regions of tissue.In other examples, processor 80 may assign voxels that are at the borderof a brain region such as the subthalamic nucleus, a value that is apercentage of the value of voxels that are 100 percent within theregion, corresponding to the percentage of the volume of the voxels thatare within the region times the value for voxels that are 100 percentwithin the region.

As another example, electrical stimulation of the anterior limb of theinternal capsule and the thalamus may be associated with adverse effectsof electrical stimulation (e.g., muscle contractions or paresthesia inthe face). Thus, processor 80 may assign each voxel that sits within theanterior limb of the internal capsule and the thalamus a relatively lowvalue (e.g., a 0 on a scale of 0-3, or, in some examples, a negativevalue on a scale from −3 to 0, in which 0 is the highest value). Thenegative scoring system may be used to help differentiate between theregions associated with therapeutic effects of stimulation and theregions associated with adverse effects. Other techniques for assigningeach voxel a value may be used.

The voxels within a particular structure within brain 28 or other tissuesite may have different values, depending on, for example, the proximityof the portion of the structure or other tissue site represented by thevoxel to regions of tissue associated with efficacious electricalstimulation therapy and to regions of tissue associated with adverseeffects of electrical stimulation. If, for example, a voxel is close toa region of tissue associated with adverse effects, but is still in aregion associated with efficacious therapy delivery, the voxel may beassigned a lower value than if the voxel was further from the region oftissue associated with adverse effects. As discussed below, the voxelvalues may be updated periodically based on information regarding theefficacy and adverse effects of electrical stimulation therapy.

In order to determine whether the VTA and the one or more regions oftissue overlap (block 106 in FIG. 4), processor 80 may compare the scoreto a threshold score value (134), which may be stored by memory 82 ofprogrammer 14 or a memory of another device. In some examples, thethreshold score value may differ depending on whether processor 80 isdetermining whether there is overlap between the VTA and one or moreefficacy regions or one or more adverse-effects regions. For example,processor 80 may compare the score to a first threshold score value todetermine whether there is overlap between the VTA and an efficacyregion and compare the score to a second threshold score value todetermine whether there is overlap between the VTA and anadverse-effects region. In some examples, the first threshold scorevalue may be higher than the second threshold score value.

In some examples, processor 80 may determine that there is overlapbetween the VTA and one or more first regions (136, as well as “YES”branch of block 106 in FIG. 4) in response to determining the score isgreater than (or, in some examples, greater than or equal to) the firstthreshold score value. The score greater than or equal to the firstthreshold score value may indicate, for example, that the VTA layssufficiently within the first region (or multiple first regions) toconstitute an overlap. On the other hand, in response to determining thescore is less than (or, in some examples, less than or equal to) thefirst threshold score value, processor 80 may determine that there is nooverlap between the VTA and the one or more first regions (“NO” branchof block 106 in FIG. 4).

In some examples in which the voxels of the 3D grid that sit in regionsof brain 28 associated with adverse effects of stimulation have negativevalues, the score computed by processor 80 may be negative or null.Processor 80 may determine that there is overlap between the VTA and theone or more second regions (136, as well as “YES” branch of block 116 inFIG. 4) in response to determining the score is less than (or, in someexamples, less than or equal to) the second threshold score value, whichmay be a negative value in some examples and a positive value in otherexamples. The score less than or equal to the second threshold scorevalue may indicate, for example, that the VTA sits sufficiently withinthe second region of tissue to constitute an overlap. On the other hand,in response to determining the score is greater than (or, in someexamples, greater than or equal to) the second threshold score value,processor 80 may determine that there is no overlap between the VTA andthe second region (136) (“NO” branch of block 116 in FIG. 4).

In some cases, processor 80 (or another processor) updates the voxelvalues of the 3D grid, e.g., after a first programming session withpatient 12, based on the actual experience of patient 12 with one ormore sets of electrical stimulation parameter values. For example, ifdelivery of electrical stimulation by IMD 16 via a selected subset ofelectrodes 24, 26 and according to a particular set of electricalstimulation parameter values resulted in efficacious electricalstimulation therapy, then processor 80 may increase the values assignedto the voxels that sit within the VTA expected to result from thedelivery, by the subset of electrodes 24, 26, of electrical stimulationaccording to the set of electrical stimulation parameter values. Inaddition, if delivery of electrical stimulation by IMD 16 via a selectedsubset of electrodes 24, 26 and according to the set of electricalstimulation parameter values resulted in inefficacious electricalstimulation therapy, adverse effects, or both, then processor 80 maydecrease the values assigned to the voxels that sit within the VTA. Theeffects of the electrical stimulation may be observed by the clinician,reported by patient 12, or determined based on the output of one or moresensors that indicate one or more physiological parameters of patient12.

The ability to increase or decrease the voxel values based on theresults of the actual delivery of electrical stimulation to patient 12may help generate a patient-specific grid (also referred to herein as a“map”). In addition, to help further personalize the grid to patient 12,the amount by which the voxel values or increased or decreased may bebased on patient specific criteria. For example, the decrease in thevalues of the VTA-overlapping voxels in a given region of tissueassociated with adverse effects of stimulation can be greater to theextent that the side-effect associated with that region is one aboutwhich patient 12 is particularly concerned, e.g., because patient 12finds that side-effect particularly intolerable.

In some cases, after updating the voxel values of a grid, processor 80may update stored therapeutic windows (or just the efficacy thresholdand adverse-effects threshold), e.g., by redetermining the therapeuticwindows based on an updated grid. In this way, the therapeutic windowsstored by memory 82 (or another memory) may be modified over time as theexperience of patient 12 with the DBS (or other electrical stimulationtherapy) changes over time, as the patient condition changes (e.g.,progresses or improves), or both. Again, in some cases, a clinician mayinteract with programmer 14 to cause processor 80 to determine thetherapeutic windows in advance of an in-clinic programming session withpatient 12, which may help reduce the amount of time required to programIMD 16.

In other examples of the technique shown in FIG. 5, processor 80 maydetermine the score based on the extent to which the VTA sits within theone or more regions of tissue. For example, processor 80 may determinewhether there is overlap between the VTA and the one or more regions oftissue if, for example, the percentage of the region(s) of tissuecovered by the VTA is greater than (or, in some examples, greater thanor equal to) a threshold score value. As another example, processor 80may determine whether there is overlap between the VTA and the one ormore regions of tissue if, for example, the number of voxels common toat least one of the regions of tissue and the VTA is greater than (or,in some examples, greater than or equal to) a threshold number. In thisexample, the voxels of the 3D grid may or may not be associated withrespective values.

In examples discussed herein, processor 80 (or a processor of anotherdevice, such as IMD 16) may determine the effect of the electricalstimulation delivered by a selected one of electrodes 24, 26 on tissueof patient 12 based on a VTA expected to result from the electricalstimulation delivered by the selected electrode, the electricalstimulation being generated in accordance with a particular set ofelectrical stimulation parameter values. Processor 80 may determine theVTA by modeling the effects of the electrical stimulation on issue inorder to determine the tissue of the patient that will be activated bythe electrical stimulation. In some examples, the VTA is defined by thetissue of patient 12 that will be activated by the electricalstimulation.

FIG. 6 is a flow diagram of an example technique for determining a VTA.In accordance with the technique shown in FIG. 6, processor 80 receivespatient anatomy data necessary for creating an electrical field model(140). The patient anatomy data indicates one or more characteristics oftissue proximate the selected electrode. The tissue proximate theselected electrode may be identified based on the known location ofleads 20 within patient 12 or, if leads 20 are not implanted in patient12, a target location of leads 20. For example, given a patient's MM andpost-operative CT scan, processor 80 can determine the position of lead20 in brain 28 and, therefore, the anatomical structures proximate theimplanted electrodes 24, 26. As another example, given a patient's MMand post-operative CT scan, processor 80 can determine the anatomicalstructures proximate the target location of electrodes 24, 26 of leads20, even if leads 20 have not yet been implanted in patient 12.

The patient anatomy data may be specific to or customized for patient12, or may be more general (e.g., generic physical characteristics ofhuman tissue applicable to a plurality of patients). In some examples,the patient anatomy data includes an anatomical image of target therapydelivery site within patient 12, a reference anatomical image, which maynot be specific to patient 12, an anatomical atlas indicating specificstructures of the patient's anatomy or a map of the tissuecharacteristics (e.g., conductivity or density) adjacent to electrodes24, 26 of leads 20. The patient anatomy data may be created based ondata generated by medical imaging, such as, but not limited to, CT, MM,or any other volumetric imaging system. Processor 60 may store thepatient anatomy data within section 92 of memory 82 (FIG. 3).

Processor 80 may model the effect of the electrical stimulationdelivered by the selected electrode on tissue of patient 12. In theexample shown in FIG. 6, processor 80 determines an electrical fieldmodel (142) that indicates the electrical field that will propagate awayfrom the electrode when an electrical stimulation signal defined by theset of electrical stimulation parameter values is delivered by theelectrode. Processor 80 may, for example, implement an algorithm (e.g.,stored as a VTA algorithm 96 in memory 82 of programmer 14) to determinethe electrical field model. The algorithm may take the received patientanatomy data into consideration, along with electrical field modelequations that define electrical current propagation in order todetermine how the electrical current will propagate away from theselected electrode.

Tissue variation within brain 28 (or other site within patient 12) maychange the electrical current propagation from the electrode in somedirections. These variations may contribute to varying therapeuticwindows of electrodes 24, 26 of leads 20. Thus, the electrical fieldmodel equations take into consideration the physical tissuecharacteristics of the tissue adjacent electrodes 24, 26 of leads 20,which is included in the patient anatomy data 92. From this information,processor 80 may estimate an electrical field that will be produced intherapy delivery via the selected electrode when IMD 16 generates anelectrical stimulation signal in accordance with the set of electricalstimulation parameter values.

In some examples, processor 80 determines the characteristics (e.g.,size, shape, and power distribution) of the electrical field based ongeneric physical characteristics of human tissue and known physicalcharacteristics of the electrodes 24, 26 of leads 20. However, in someexamples, processor 80 determines the characteristics of the electricalfield based on the actual anatomical structure of patient 12 beingtreated. While in either example, the electrical field model may be anapproximation of what the electrical field would be in brain 28 of aspecific patient 12, the electrical field model determined based on theactual anatomical structure of patient 12 may be a more accuraterepresentation of the electrical field that will result from thedelivery of electrical stimulation via the selected electrode.

In the technique shown in FIG. 6, processor 80 determines a neuron model(144). The neuron model indicates, for each of a plurality of volumes oftissue of patient 12, the voltage or current amplitude that is requiredfor the tissue to be stimulated. For example, the neuron model may be a3D grid of voxels, and each voxel may be associated with a voltage orcurrent amplitude that is required for tissue within the particularvoxel to be stimulated. As another example, the neuron model may includea grid of 2D areas, where each area of the grid may be associated with avoltage or current amplitude that is required for tissue within theparticular area to be stimulated. In some examples, processor 80determines the neuron model by generating the neuron model, e.g., basedon tissue impedance characteristics of patient 12 determined usingmedical imaging and stored as patient anatomy data 92 (FIG. 3) or basedon tissue impedance characteristics for a general atlas of brain 28. Inother examples, the neuron model is predetermined by another processorand stored by memory 82 of programmer 14 (or another memory of anotherdevice); processor 80 may determine the neuron model by retrieving itfrom the memory.

Processor 80 determines an activation field model based on theelectrical field model and the neuron model (146). The activation fieldmodel may indicate which tissue of patient 12 will be activated (e.g.,stimulated) by the electrical field expected to be generated from thedelivery of electrical stimulation. In some examples, processor 80determines the activation field model based on a fit between the neuronmodel and the electrical field model. The electrical field expected toresult from delivery of electrical stimulation by the selected electrodeand according to a particular set of electrical stimulation parametersmay have an intensity too low to activate the neurons in at least sometissue proximate the selected electrode. Thus, by fitting the neuronmodel and the electrical field model to each other, processor 80 maydetermine the volume of tissue that is expected to be activated ifelectrical stimulation is delivered by the selected electrode to atarget tissue location with specified electrical stimulation parametervalues.

FIG. 7 is a flow diagram of another example technique that processor 80may implement to determine therapeutic windows for one or moreelectrodes 24, 26. FIG. 7 illustrates an example technique fordetermining the efficacy threshold and adverse-effects threshold for anelectrode or electrode combination, and may be an example of thetechnique shown in FIG. 4.

In the technique shown in FIG. 7, processor 80 selects an electrode 24,26 (or electrode combination in some examples) (100). Processor 80selects an initial stimulation amplitude value for determining thethresholds and sets the efficacy threshold and adverse-effects thresholdassociated with the electrode in memory 82 to unknown (150), such thatthe selected electrode is not associated with an efficacy threshold oran adverse-effects threshold in memory 82. The initial stimulationamplitude value may be a value known to be less than an efficacythreshold value and an adverse-effects threshold value. For example, insome examples, the initial stimulation amplitude value is zero. Othernominal stimulation amplitude values may also be used as the initialvalue.

Processor 80 determines whether both the efficacy and adverse-effectsthresholds for the selected electrode are known (152). In response todetermining both thresholds are known (“YES” branch of block 152),processor 80 determines the therapeutic window for the selectedelectrode based on the known efficacy and adverse-effects thresholds(154). For example, processor 80 may use the technique described withrespect to FIG. 8 to determine the therapeutic window.

On the other hand, in response to determining that it is not true thatboth thresholds are known (“NO” branch of block 152), processor 80determines whether the stimulation amplitude is greater than apredetermined maximum (156). The predetermined maximum value for thestimulation amplitude (or other stimulation parameter value orcombination of values with which the therapeutic window is defined) canbe, for example, stored by memory 82. The predetermined maximum valuecan be selected using any suitable techniques. In some examples, aclinician may select the predetermined maximum value to be the amplitudevalue (or other stimulation parameter value or combination of values) atwhich the stimulation intensity is at a maximum desired intensity forpatient 12 or a group of patients. As another example, a clinician mayselect the predetermined maximum value to be the amplitude value to bethe maximum amplitude value permitted by the hardware, software, orboth, of IMD 16.

If the stimulation amplitude is greater than the predetermined maximum(“YES” branch of block 156), then processor 80 may cease any furtherdetermination of the efficacy and adverse-effects thresholds. To theextent the efficacy threshold is not yet known by the time thestimulation amplitude has been increased to be greater than thepredetermined maximum, processor 80 may determine that the efficacythreshold is relatively high and unknown. To the extent theadverse-effects threshold is not yet known by the time the stimulationamplitude has been increased to be greater than the predeterminedmaximum, processor 80 may determine that the adverse-effects thresholdis relatively high. As described with respect to FIG. 8, in some cases,processor 80 may set the adverse-effects threshold to a relatively highvalue.

In response to determining the stimulation amplitude is greater than(or, in some examples, greater than or equal to) the predeterminedmaximum (“YES” branch of block 156), processor 80 determines thetherapeutic window for the selected electrode based on the efficacy andadverse-effects thresholds that may have already been determined for theselected electrode (154). Processor 80 may use the technique describedwith respect to FIG. 8 to determine the therapeutic window, even if oneof the thresholds may not be known, e.g., because the stimulationamplitude reached the predetermined maximum before the threshold valuewas reached.

In response to determining the stimulation amplitude is less than orequal to (or, in some examples, less than) the predetermined maximum(“NO” branch of block 156), processor 80 may determine a VTA based onthe selected amplitude value (158), e.g., as described above withrespect to FIG. 4. Processor 80 compares the VTA and one or more firstregions (160) and determines whether the commonality is sufficient orsignificant enough to constitute an overlap, e.g., using the techniquesdescribed with respect to FIG. 5 (162). The commonality of tissuebetween the VTA and one or more first regions may be sufficient orsignificant enough to constitute an overlap if, for example, thecommonality amounts to at least a predetermined threshold volume whensummed. As another example, processor 80 may determine the commonalityof tissue between the VTA and one or more first regions is sufficient orsignificant enough to constitute an overlap in response to determiningthe score of the voxels that are common to the VTA and the one or morefirst regions is greater than or equal to a predetermined thresholdscore.

Processor 80 also determines whether the efficacy threshold value isalready known, e.g., has already been determined for the selectedelectrode (162). For example, processor 80 may determine whether theselected electrode is associated with an efficacy threshold value inmemory 82 of programmer 14 (FIG. 3). In response to determining theefficacy threshold is not yet known and there is overlap between the VTAand the one or more first regions (“YES” branch of block 162), processor80 may select the stimulation amplitude (selected at block 150) as anefficacy threshold (164) and, e.g., store the efficacy threshold andassociated electrode as therapeutic window information 98 (FIG. 3) inmemory 82.

In response to determining the efficacy threshold for the selectedelectrode is already known, there is no overlap between the VTA and theone or more first regions, or both (“NO” branch of block 156), or inresponse to selecting the stimulation amplitude as the efficacythreshold (164), processor 80 may compare the VTA and one or more secondregions (166) and determine whether the commonality is sufficient orsignificant enough to constitute an overlap, e.g., using the techniquesdescribed with respect to FIG. 5 (168). The commonality of tissuebetween the VTA and one or more second regions may be sufficient orsignificant enough to constitute an overlap if, for example, thecommonality amounts to at least a predetermined threshold volume whensummed or in response to determining the score of the voxels that arecommon to the VTA and the one or more second regions is greater than orequal to a predetermined threshold score, or, in some examples, lessthan or equal to a predetermined threshold score.

In response to determining the adverse-effects threshold is unknown andthere is overlap between the VTA and the one or more second regions(“YES” branch of block 168), processor 80 selects the stimulationamplitude (selected at block 102) as the adverse-effects threshold (170)and, e.g., stores the adverse-effects threshold and associated electrodeas therapeutic window information 98 (FIG. 3) in memory 82.

In response to determining the adverse-effects threshold is known, thereis no overlap between the VTA and the one or more second regions (“NO”branch of block 168), or both, or in response to selecting thestimulation amplitude as the adverse-effects threshold (170), processor80 increases the amplitude by a predetermined increment (172). Processor80 may then determine whether both the adverse-effects threshold andefficacy thresholds are known (152) and go through the technique shownin FIG. 7 until the efficacy and adverse-effects threshold values aredetermined for the selected electrode (152), or until the stimulationamplitude is increased to be greater than the predetermined maximum(156). Processor 80 may also use the technique shown in FIG. 7 todetermine the efficacy threshold and adverse-effects thresholds forother electrodes 24, 26 of system.

After implementing the technique shown in FIG. 7, processor 80 maydetermine the therapeutic window for an electrode, e.g., using thetechnique shown in FIG. 8. FIG. 8 is a flow diagram of an exampletechnique for determining the therapeutic window for an electrode.Processor 80 may implement the technique shown in FIG. 8 for at leastone electrode 24, 26, e.g., each electrode 24, 26.

As shown in FIG. 8, in some examples, processor 80 identifies theefficacy threshold, adverse-effects threshold, or both, for a selectedelectrode 24, 26 (174). For example, processor 80 may determine whetherthe electrode is associated with an efficacy threshold, adverse-effectsthreshold, or both in memory 82 of programmer 14. Processor 80 maydetermine the efficacy threshold, the adverse-effects threshold, orboth, and associate the electrode with the determined thresholds inmemory 82, e.g., using the one or both techniques described with respectto FIGS. 4 and 7.

Based on the identified thresholds, processor 80 determines, whether theefficacy threshold value is known (176). For example, processor 80 maydetermine whether the selected electrode is associated with an efficacythreshold in memory 82 of programmer 14 (FIG. 3). In response todetermining the efficacy threshold is known (“YES” branch of block 176)or in response to determining the efficacy threshold is not known (“NO”branch of block 176), processor 80 determines whether theadverse-effects threshold is known (178, 180, respectively). As with theefficacy threshold, processor 80 may determine whether theadverse-effects threshold is known based on whether the selectedelectrode is associated with an adverse-effects threshold in memory 82of programmer 14 (FIG. 3).

If neither the efficacy threshold nor the adverse-effects threshold areknown, processor 80 may determine that the therapeutic window cannot bedetermined at that time for the selected electrode. Thus, in response todetermining the adverse-effects threshold is not known (“NO” branch ofblock 180), processor 80 sets the therapeutic window for the selectedelectrode to unknown (182). Processor 80 may associate the selectedelectrode with the indication of an unknown therapeutic window in memory82.

If the efficacy threshold was not determined for the electrode, but theadverse-effects threshold was determined, then processor 80 maydetermine that the therapeutic window for the selected electrode iszero. For example, processor 80 may determine that the selectedelectrode is not implanted in patient 12 at a location that permits theelectrode to deliver efficacious electrical stimulation therapy. The VTAresulting from the electrical stimulation delivered by the electrode maynot overlap with any efficacy regions, but may overlap with one or moreadverse-effects regions. Thus, in response to determining theadverse-effects threshold is known (“YES” branch of block 180),processor 80 sets the therapeutic window for the selected electrode tozero (184). Processor 80 may associate the selected electrode with atherapeutic window size of zero in memory 82.

If the efficacy threshold is known, but the adverse-effects threshold isnot known (“NO” branch of block 178), then processor 80 may determinethat the that the selected electrode is not implanted in patient 12 at alocation that causes the electrical stimulation delivered by theelectrode to cause any side effects. The VTA resulting from theelectrical stimulation delivered by the electrode may not overlap withany adverse-effects regions, but may overlap with one or more efficacyregions. Thus, in response to determining the adverse-effects thresholdis not known (“NO” branch of block 178), processor 80 sets theadverse-effects threshold to a predetermined maximum value plus apredetermined increment (186).

The predetermined increment can be, for example, the increment withwhich the stimulation amplitude value was increased in the techniquesshown in FIGS. 4 and 7 or another increment value. After setting theadverse-effects threshold (186), processor 80 sets the therapeuticwindow for the selected electrode based on the known efficacy andadverse-effects thresholds (188). Processor 80 may associate theselected electrode with the therapeutic window in memory 82.

If both the efficacy and adverse-effects thresholds are known (“YES”branch of block 178), then processor 80 may determine whether theefficacy threshold value is less than or equal to the adverse-effectsthreshold value (190). In response to determining the efficacy thresholdvalue is less than or equal to the adverse-effects threshold value(“YES” branch of block 190), processor 80 sets the therapeutic windowfor the selected electrode based on the efficacy and adverse-effectsthreshold values (188). On the other hand, in response to determiningthe efficacy threshold value is not less than or equal to theadverse-effects threshold value (“NO” branch of block 178), processor 80sets the therapeutic window to zero (184). In some examples, an efficacythreshold value that is greater than the adverse-effects threshold mayindicate that, in order for the delivery of electrical stimulation bythe selected electrode to cause one or more efficacious effects, thestimulation may also cause one or more adverse effects.

While the techniques described with respect to FIGS. 4-8 are primarilydescribed as being used to determine a therapeutic window for eachindividual electrode 24, 26 based on a VTA expected to result fromelectrical stimulation delivered via the respective individual electrodein a unipolar configuration (e.g., with the housing of IMD 16 acting asa reference electrode), in other examples, the devices, systems, andtechniques described herein may be used to determine the therapeuticwindow for each of a plurality of electrode combinations being definedby select electrodes of electrodes 24, 26. The electrode combinationscould be used to, for example, provide bipolar, omnipolar, or multipolarelectrical stimulation, or any combination thereof.

For example, rather than selecting a single electrode and determiningthe therapeutic window based on the VTA resulting from delivery ofelectrical stimulation with the single electrode in a unipolarcombination, processor 80 may select an electrode combination (e.g., abipolar electrode combination, or an electrode combination includingthree or more electrodes), and determine the efficacy threshold andadverse-effects threshold based on the VTA expected to result from thedelivery of electrical stimulation therapy with the electrodecombination (e.g., using the techniques described above) and the set ofelectrical stimulation parameters. For a particular electrodecombination, processor 80 may determine an initial VTA based on a set ofelectrical stimulation parameter values, and adjust (e.g., increase ordecrease in predetermined increments) the value of at least one of thestimulation parameters of the set until the resulting VTA overlaps withone or more efficacy regions of tissue to determine the efficacythreshold for the at least one stimulation parameter. Processor 80 maythen continuing adjusting the value of the at least one stimulationparameter (e.g., in predetermined increments) until the resulting VTAoverlaps with one or more adverse-effects regions to determine theadverse-effects threshold. The amount of commonality in space betweenthe VTA and the one or more regions of tissue required to constitute anoverlap may be the same as that described above with respect to FIGS.4-8.

Processor 80 may then associate the electrode combination andtherapeutic window (or efficacy and adverse-effects threshold values)and store the information in memory 82 of programmer 14 or anothermemory.

The techniques described herein for associating individual electrodes orelectrode combinations with a therapeutic window (or with efficacy andadverse-effects threshold values) may be performed pre-operatively,before leads 20 are implanted in patient 12, or post-operatively, afterleads 20 are implanted in patient 12. For example the techniquesdescribed with respect to FIGS. 4-8 may be performed before leads 20 areimplanted in patient 12, based on a selected target location for thefuture implantation of leads 20, or after leads 20 are implanted inpatient 12, based on the known location of leads 20 within patient 12.Determining the therapeutic windows (or with efficacy andadverse-effects threshold values) before leads 20 are implanted inpatient 12 may enable a starting point for programming IMD 16 to beestablished before leads 20 are even implanted in patient 12.

While the techniques described above are primarily described as beingperformed by processor 60 of IMD 16 or processor 80 of programmer 14, inother examples, one or more other processors may perform any part of thetechniques described herein alone or in addition to processor 60 orprocessor 80. Thus, reference to “a processor” may refer to “one or moreprocessors.” Likewise, “one or more processors” may refer to a singleprocessor or multiple processors in different examples.

The techniques described in this disclosure, including those attributedto IMD 16, programmer 14, or various constituent components, may beimplemented, at least in part, in hardware, software, firmware or anycombination thereof. For example, various aspects of the techniques maybe implemented within one or more processors, including one or moremicroprocessors, DSPs, ASICs, FPGAs, or any other equivalent integratedor discrete logic circuitry, as well as any combinations of suchcomponents, embodied in programmers, such as clinician or patientprogrammers, medical devices, or other devices.

In one or more examples, the functions described in this disclosure maybe implemented in hardware, software, firmware, or any combinationthereof. If implemented in software, the functions may be stored on, asone or more instructions or code, a computer-readable medium andexecuted by a hardware-based processing unit. Computer-readable mediamay include computer-readable storage media forming a tangible,non-transitory medium. Instructions may be executed by one or moreprocessors, such as one or more DSPs, ASICs, FPGAs, general purposemicroprocessors, or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used herein may referto one or more of any of the foregoing structure or any other structuresuitable for implementation of the techniques described herein.

In addition, in some aspects, the functionality described herein may beprovided within dedicated hardware and/or software modules. Depiction ofdifferent features as modules or units is intended to highlightdifferent functional aspects and does not necessarily imply that suchmodules or units must be realized by separate hardware or softwarecomponents. Rather, functionality associated with one or more modules orunits may be performed by separate hardware or software components, orintegrated within common or separate hardware or software components.Also, the techniques could be fully implemented in one or more circuitsor logic elements. The techniques of this disclosure may be implementedin a wide variety of devices or apparatuses, including an IMD, anexternal programmer, a combination of an IMD and external programmer, anintegrated circuit (IC) or a set of ICs, and/or discrete electricalcircuitry, residing in an IMD and/or external programmer.

Various examples have been described. These and other examples arewithin the scope of the following claims.

What is claimed is:
 1. A method comprising: receiving, by a processor,an input indicative of at least one of an efficacious result or anadverse-effect result of a delivery of electrical stimulation therapy toa patient by a medical device according to at least one electricalstimulation parameter value; determining, by the processor, a volume oftissue activation expected to result from the delivery of electricalstimulation to the patient according to the at least one electricalstimulation parameter value; determining, by the processor, one or morevoxels of a grid that overlap with the volume of tissue activation,wherein the grid comprises a plurality of voxels, and wherein each voxelof the plurality of voxels is associated with a respective voxel value;and modifying, by the processor and based on the input, a voxel value ofat least one of the one or more voxels of the grid that overlap with thevolume of tissue activation.
 2. The method of claim 1, wherein the inputis based on a sensed physiological signal of the patient.
 3. The methodof claim 2, wherein the sensed physiological signal of the patientcomprises a bioelectrical brain signal of the patient.
 4. The method ofclaim 2, further comprising sensing, by a sensing module, thephysiological signal of the patient.
 5. The method of claim 1, whereinreceiving the input comprises receiving the input via a user interface.6. The method of claim 1, further comprising controlling the medicaldevice to deliver the electrical stimulation therapy to the patientaccording to the at least one electrical stimulation parameter value. 7.The method of claim 1, wherein determining, by the processor, the one ormore voxels of the grid that overlap with the volume of tissueactivation comprises registering, by the processor, the volume of tissueactivation to the grid, wherein the grid corresponds to at least oneregion of a brain of the patient.
 8. The method of claim 1, wherein theinput is indicative of the efficacious result, and wherein modifying thevoxel value comprises increasing the voxel value of the at least one ofthe one or more voxels based on the input.
 9. The method of claim 8,further comprising determining, by the processor, whether the at leastone of the one or more voxels is fully within the volume of tissueactivation, wherein increasing the voxel value comprises one ofincreasing the voxel value by a first value based on determining thatthe at least one of the one or more voxels is fully within the volume oftissue activation, or increasing the voxel value by a second value basedon determining that the at least one of the one or more voxels ispartially within the volume of tissue activation, wherein the secondvalue is less than the first value.
 10. The method of claim 1, whereinthe input is indicative of the adverse-effect result, and whereinmodifying the voxel value comprises decreasing the voxel value of the atleast one of the one or more voxels based on the input.
 11. The methodof claim 1, further comprising: determining, by the processor and aftermodifying the voxel value, a score based on the values associated withthe plurality of voxels of the grid, wherein the score represents anoutcome of the electrical stimulation therapy delivered to the patientaccording to the at least one electrical stimulation parameter value,and selecting, by the processor and based on the score, at least oneupdated electrical stimulation parameter value for the electricalstimulation therapy.
 12. The method of claim 11, wherein the inputcomprises a first input and the volume of tissue activation comprises afirst volume of tissue activation, the method further comprising:receiving, by the processor, a second input indicative of at least oneof an efficacious result and an adverse-effect result of the delivery ofelectrical stimulation therapy to the patient by the medical deviceaccording to the at least one updated electrical stimulation parametervalue; determining, by the processor, a second volume of tissueactivation expected to result from the delivery of electricalstimulation to the patient according to the at least one updatedelectrical stimulation parameter value; determining, by the processor,one or more voxels of the grid that overlap with the second volume oftissue activation; and modifying, by the processor and based on thesecond input, a voxel value of at least one of the one or more voxels ofthe grid that overlap with the second volume of tissue activation. 13.The method of claim 12, further comprising controlling the medicaldevice to deliver the electrical stimulation therapy to the patientaccording to the at least one updated electrical stimulation parametervalue.
 14. The method of claim 1, further comprising selecting, by theprocessor, the grid from a plurality of grids associated with respectivemedical conditions, wherein selecting the grid comprises selecting thegrid from the plurality of grids based on a medical condition of thepatient.
 15. The method of claim 1, wherein the volume of tissueactivation represents a volume of tissue within a brain of the patient.16. The method of claim 1, wherein the grid comprises athree-dimensional grid, and wherein each voxel of the plurality ofvoxels represents a three-dimensional volume of tissue.
 17. A systemcomprising: a memory that stores a grid comprising a plurality ofvoxels, wherein each voxel of the plurality of voxels is associated witha respective voxel value; and a processor configured to: receive aninput indicative of at least one of an efficacious result or anadverse-effect result of a delivery of electrical stimulation therapy toa patient by a medical device according to at least one electricalstimulation parameter value, determine a volume of tissue activationexpected to result from the delivery of electrical stimulation to thepatient according to the at least one electrical stimulation parametervalue, determine one or more voxels of the grid that overlap with thevolume of tissue activation, and modify, based on the input, a voxelvalue of at least one of the one or more voxels of the grid that overlapwith the volume of tissue activation.
 18. The system of claim 17,wherein the input is based on a sensed physiological signal of thepatient.
 19. The system of claim 18, wherein the sensed physiologicalsignal of the patient comprises a bioelectrical brain signal of thepatient.
 20. The system of claim 18, further comprising a sensing moduleconfigured to sense the physiological signal of the patient.
 21. Thesystem of claim 17, further comprising a user interface, wherein theprocessor is configured to receive the input via the user interface. 22.The system of claim 17, further comprising the medical device, whereinthe processor is further configured to control the medical device todeliver the electrical stimulation therapy to the patient according tothe at least one electrical stimulation parameter value.
 23. The systemof claim 17, wherein the processor is configured to determine the one ormore voxels of the grid that overlap with the volume of tissueactivation by at least registering the volume of tissue activation tothe grid, wherein the grid corresponds to at least one region of a brainof the patient.
 24. The system of claim 17, wherein the input isindicative of the efficacious result, and wherein the processor isconfigured to modify the voxel value by at least increasing the voxelvalue of the at least one of the one or more voxels based on the input.25. The system of claim 24, wherein the processor is configured todetermine whether the at least one of the one or more voxels is fullywithin the volume of tissue activation, and increase the voxel value ofthe at least one of the one or more voxels by one of increasing thevoxel value by a first value based on determining that the at least oneof the one or more voxels is fully within the volume of tissueactivation, or increasing the voxel value by a second value based ondetermining that the at least one of the one or more voxels is partiallywithin the volume of tissue activation, wherein the second value is lessthan the first value.
 26. The system of claim 17, wherein the input isindicative of the adverse-effect result, and wherein the processor isconfigured to modify the voxel value by at least decreasing the voxelvalue of the at least one of the one or more voxels based on the input.27. The system of claim 17, wherein the processor is further configuredto: determine, after modifying the voxel value of the one or more voxelsof the grid that overlap with the volume of tissue activation, a scorebased on the values associated with the plurality of voxels of the grid,wherein the score represents one of an outcome of the electricalstimulation therapy delivered to the patient according to the at leastone electrical stimulation parameter value, and select, based on thescore, at least one updated electrical stimulation parameter value forthe electrical stimulation therapy.
 28. The system of claim 27, whereinthe input comprises a first input and the volume of tissue activationcomprises a first volume of tissue activation, wherein the processor isfurther configured to: receive a second input indicative of at least oneof an efficacious result and an adverse-effect result of the delivery ofelectrical stimulation therapy to the patient by the medical deviceaccording to the at least one updated electrical stimulation parametervalue, determine a second volume of tissue activation expected to resultfrom the delivery of electrical stimulation to the patient according tothe at least one updated electrical stimulation parameter value,determine one or more voxels of the grid that overlap with the secondvolume of tissue activation, and modify, based on the second input, avoxel value of at least one of the one or more voxels of the grid thatoverlap with the second volume of tissue activation.
 29. The system ofclaim 28, further comprising the medical device, wherein the processoris further configured to control the medical device to deliver theelectrical stimulation therapy to the patient according to the at leastone updated electrical stimulation parameter value.
 30. The system ofclaim 17, wherein the processor is further configured to select the gridfrom a plurality of grids stored by the memory based on a medicalcondition of the patient, the plurality of grids being associated withrespective medical conditions.
 31. The system of claim 17, wherein thevolume of tissue activation represents a volume of tissue within a brainof the patient.
 32. The system of claim 17, wherein the grid comprises athree-dimensional grid, and wherein each voxel of the plurality ofvoxels represents a three-dimensional volume of tissue.
 33. A systemcomprising: means for receiving an input indicative of at least one ofan efficacious result or an adverse-effect result of a delivery ofelectrical stimulation therapy to a patient by a medical deviceaccording to at least one electrical stimulation parameter value; meansfor determining a volume of tissue activation expected to result fromthe delivery of electrical stimulation to the patient according to theat least one electrical stimulation parameter value; means fordetermining one or more voxels of a grid that overlap with the volume oftissue activation, wherein the grid comprises a plurality of voxels, andwherein each voxel of the plurality of voxels is associated with arespective voxel value; and means for modifying, based on the input, avoxel value of at least one of the one or more voxels of the grid thatoverlap with the volume of tissue activation.
 34. A non-transitorycomputer-readable medium comprising instructions that, when executed bya processor, cause the processor to: receive an input indicative of atleast one of an efficacious result or an adverse-effect result of adelivery of electrical stimulation therapy to a patient by a medicaldevice according to at least one electrical stimulation parameter value;determine a volume of tissue activation expected to result from thedelivery of electrical stimulation to the patient according to the atleast one electrical stimulation parameter value; determine one or morevoxels of a grid that overlap with the volume of tissue activation,wherein the grid comprises a plurality of voxels, and wherein each voxelof the plurality of voxels is associated with a respective voxel value;and modify, based on the input, a voxel value of at least one of the oneor more voxels of the grid that overlap with the volume of tissueactivation.